阅读说明：本技术 风化壳岩溶储层的储能系数预测方法及装置 (Energy storage coefficient prediction method and device for weathering crust karst reservoir ) 是由 戴晓峰 甘利灯 张明 姜晓宇 杜本强 隆辉 牟川 江林 王浩 于 2021-01-05 设计创作，主要内容包括：本发明公开了一种风化壳岩溶储层的储能系数预测方法及装置,该方法包括：提取待预测储层的地震数据的地震振幅属性值,利用拟合后得到的储能系数和地震振幅属性值之间的转换关系,预测获得待预测储层的储能系数。本发明通过拟合储能系数和地震振幅属性值之间的转换关系,进而直接预测风化壳岩溶储层的储能系数,能够提高风化壳岩溶储层的储能系数预测的精度。(The invention discloses a method and a device for predicting an energy storage coefficient of a weathering crust karst reservoir, wherein the method comprises the following steps: and extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted, and predicting and obtaining the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the method, the energy storage coefficient of the weathering crust karst reservoir can be directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the prediction precision of the energy storage coefficient of the weathering crust karst reservoir can be improved.)

1. A method for predicting the energy storage coefficient of a weathering crust karst reservoir is characterized by comprising the following steps:

extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted;

and predicting and obtaining the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

2. The method for predicting the energy storage coefficient of a reservoir of weathering crust karst of claim 1, further comprising:

carrying out strong reflection shielding removal processing on the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after shielding removal;

extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted, wherein the extracting comprises the following steps:

and extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding is removed.

3. The method of predicting energy storage coefficients for a reservoir of litholytic weathering of claim 1, wherein fitting a transformed relationship between energy storage coefficients and seismic amplitude attribute values includes:

determining a three-dimensional forward seismic record of a target sample reservoir according to seismic data of the target sample reservoir;

extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a longitudinal measuring line serial number value and a transverse measuring line serial number value corresponding to the seismic amplitude attribute value;

determining the energy storage coefficient of the target sample reservoir according to the longitudinal measuring line sequence number value and the transverse measuring line sequence number value corresponding to the seismic amplitude attribute value;

and carrying out intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting to construct a conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

4. The method of predicting energy storage coefficients for a reservoir of litholytic weathering of claim 3, wherein fitting a transformed relationship between energy storage coefficients and seismic amplitude attribute values further comprises:

carrying out strong reflection shielding removal treatment on the three-dimensional forward seismic record of the target sample reservoir along the weathering crust to obtain the three-dimensional forward seismic record after the shielding of the target sample reservoir is removed;

the method for extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value comprises the following steps:

and extracting the seismic amplitude attribute value of the three-dimensional forward modeling seismic record after the target sample reservoir is subjected to shielding removal, and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value.

5. The method for predicting the energy storage coefficient of a reservoir of weathering crust karst according to claim 3, wherein determining the three-dimensional forward seismic record of the target sample reservoir from the seismic data of the target sample reservoir includes:

acquiring seismic data of a target sample reservoir;

acquiring seismic wavelets of a target sample reservoir according to seismic data of the target sample reservoir;

constructing a three-dimensional wave impedance model of the target sample reservoir about reservoir thickness, reservoir porosity and time;

and performing seismic forward modeling by using the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelets to obtain three-dimensional forward seismic records of the target sample reservoir.

6. The method for predicting the energy storage coefficient of the weathering crust karst reservoir of claim 5, wherein constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity, and time comprises:

acquiring logging data of a target sample reservoir;

determining an average wave impedance of an overburden formation and an average wave impedance of an underburden carbonate formation in the target sample reservoir using the log data of the target sample reservoir;

determining wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir through rock physical analysis by using the logging data of the target sample reservoir;

and establishing a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir and the wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir.

7. The method for predicting the energy storage coefficient of a weathering crust karst reservoir of claim 6, wherein constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity, and time further comprises:

determining the reservoir thickness maximum value and the porosity maximum value of a weathering crust karst reservoir in the target sample reservoir by using the logging data of the target sample reservoir;

the three-dimensional wave impedance model of the target sample reservoir takes the reservoir thickness change direction as a longitudinal measurement line direction, the reservoir porosity change direction as a transverse measurement line direction, and the time change direction as a vertical measurement line direction;

the reservoir thickness of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum reservoir thickness along the longitudinal measuring line direction, and the porosity of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum porosity along the transverse measuring line direction.

8. The method for predicting the energy storage coefficient of the reservoir of the weathering crust karst according to claim 3, wherein the step of extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the longitudinal line serial number value and the transverse line serial number value corresponding to the seismic amplitude attribute value comprises the following steps:

determining an effective seismic response time window of a target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective seismic response time window of the target sample reservoir is the time length of the weathering crust to the bottom of the reservoir corresponding to the wave crest reflection on the seismic channel where the maximum thickness and the maximum porosity of the reservoir are located;

and extracting the seismic amplitude attribute value and the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

9. An apparatus for predicting an energy storage coefficient of a reservoir of litho-dissolved weathering crust, comprising:

the amplitude attribute extraction module is used for extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted;

and the energy storage coefficient prediction module is used for predicting and obtaining the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

10. The apparatus for predicting an energy storage coefficient of a reservoir of weathering crust karst of claim 9, further comprising:

the shielding removal processing module is used for carrying out strong reflection shielding removal processing on the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after shielding removal;

and the amplitude attribute extraction module is also used for extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding is removed.

11. The apparatus for predicting energy storage coefficients for a reservoir of weathering crust karst of claim 9, wherein fitting a conversion relationship between energy storage coefficients and seismic amplitude attribute values includes:

the seismic record determining module is used for determining the three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir;

the sample seismic amplitude extraction module is used for extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a longitudinal measurement line serial number value and a transverse measurement line serial number value corresponding to the seismic amplitude attribute value;

the sample energy storage coefficient determining module is used for determining the energy storage coefficient of the target sample reservoir according to the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value;

and the conversion relation fitting construction module is used for carrying out intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir and fitting and constructing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

12. The apparatus for predicting energy storage coefficients for a reservoir of weathering crust karst of claim 11, wherein fitting a conversion relationship between energy storage coefficients and seismic amplitude attribute values further comprises:

the sample shielding removal processing module is used for carrying out strong reflection shielding removal processing on the three-dimensional forward seismic record of the target sample reservoir along the weathering crust to obtain the three-dimensional forward seismic record after the target sample reservoir is shielded;

and the sample seismic amplitude extraction module is also used for extracting the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal, and the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value.

13. The apparatus for predicting energy storage coefficients for a reservoir of litholytic weathering of claim 11, wherein the seismic record determination module includes:

the seismic data acquisition unit is used for acquiring seismic data of a target sample reservoir;

the wavelet obtaining unit is used for obtaining seismic wavelets of the target sample reservoir according to the seismic data of the target sample reservoir;

the model building unit is used for building a three-dimensional wave impedance model of the target sample reservoir about the reservoir thickness, the reservoir porosity and the time;

and the forward modeling unit is used for performing seismic forward modeling by utilizing the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelets to obtain the three-dimensional forward seismic record of the target sample reservoir.

14. The apparatus for predicting energy storage coefficients of a reservoir of weathering crust karst of claim 13, wherein the model building unit includes:

the logging data acquisition subunit is used for acquiring logging data of the target sample reservoir;

the upper and lower stratum wave impedance determination subunit is used for determining the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir by utilizing the logging data of the target sample reservoir;

the karst reservoir wave impedance determining subunit is used for determining wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis by utilizing the logging data of the target sample reservoir;

and the model building subunit is used for building a three-dimensional wave impedance model of the target sample reservoir about the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir and the wave impedance corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir.

15. The apparatus for predicting energy storage coefficients of a reservoir of weathering crust karst of claim 14, wherein the model building unit further includes:

the maximum value determining subunit is used for determining the reservoir thickness maximum value and the porosity maximum value of the weathering crust karst reservoir in the target sample reservoir by utilizing the logging data of the target sample reservoir;

the three-dimensional wave impedance model of the target sample reservoir takes the reservoir thickness change direction as a longitudinal measurement line direction, the reservoir porosity change direction as a transverse measurement line direction, and the time change direction as a vertical measurement line direction;

the reservoir thickness of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum reservoir thickness along the longitudinal measuring line direction, and the porosity of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum porosity along the transverse measuring line direction.

16. The apparatus for predicting energy storage coefficients of a reservoir of weathering crust karst of claim 11, wherein the sample seismic amplitude extraction module includes:

the response time window determining unit is used for determining an effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective seismic response time window of the target sample reservoir is the time length of the weathering crust to the bottom of the reservoir corresponding to the wave crest reflection on the seismic channel where the maximum thickness and the maximum porosity of the reservoir are located;

and the seismic amplitude attribute extraction unit is used for extracting the seismic amplitude attribute value and the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

17. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the method for predicting storage coefficients of a reservoir of litholytic weathering shells according to any of claims 1 to 8.

18. A computer-readable storage medium storing a computer program for performing the method of predicting storage coefficients of the reservoir of weathering crust karst as claimed in any one of claims 1 to 8.

Technical Field

The invention relates to the technical field of geological exploration, in particular to a method and a device for predicting an energy storage coefficient of a weathered crust karst reservoir.

Background

This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

The ancient karst of the deep marine carbonate rock is generally developed in China, and weathered crust karst reservoirs are mainly distributed in Erdos, Tarim, Sichuan basins and the like in China, and are one of the main gas production layers of the marine hydrocarbon-bearing basins in China. Seismic prediction of a weathering crust karst reservoir mainly adopts a seismic attribute or a seismic inversion method to predict seismic facies, thickness, porosity, hydrocarbon-bearing property and sedimentary facies of the weathering crust karst reservoir, predict a favorable reservoir distribution range and support well position deployment of exploration and development.

There are many factors that affect the productivity of a reservoir of weathering crust karst, the two most important of which are the thickness and porosity of the reservoir of weathering crust karst. The porosity determines the amount of fluid contained in a reservoir layer in unit volume, and the larger the porosity is, the more fluid is contained in a pore space; the greater the reservoir thickness, the higher the oil and gas production. Clearly, neither thickness nor porosity alone is a good reflection of the potential capacity of the reservoir. In the oil and gas industry, the energy storage coefficient is the product of reservoir thickness and porosity and hydrocarbon saturation, often expressed as (h φ Sg) or (h φ So). The energy storage coefficient comprehensively reflects the characteristics of the thickness, scale, form, physical property, grade and the like of the reservoir, the size of the energy storage coefficient is closely related to the reserve capacity and the productivity, and the energy storage coefficient is a good parameter for oil gas enrichment and capacity prediction. Therefore, compared with single porosity or reservoir thickness, the energy storage coefficient is more suitable for the capacity prediction of the low-porosity and low-permeability reservoir formed by weathered crust karst.

At present, a few examples of energy storage coefficient prediction by utilizing seismic data are available, and the method mainly comprises the steps of respectively predicting the porosity and the thickness of a reservoir by utilizing the seismic data, and multiplying the porosity and the thickness to obtain the energy storage coefficient. For example, in 2004, the daylily selects seismic attributes, the porosity and the effective thickness of a reservoir are respectively predicted, and the porosity and the effective thickness are multiplied to obtain an energy storage coefficient distribution prediction graph. In 2004, the thickness and the porosity of a reservoir stratum on a plane are obtained by respectively inverting the shewang and the arene, and then the thickness and the porosity are jointly calculated to obtain an energy storage coefficient. In 2017, the Jajiuwei application model iteratively inverts and predicts the thickness of the reservoir, predicts the porosity based on speed inversion, and finally performs mathematical product operation on the thickness and the porosity result to obtain the energy storage coefficient.

In recent years, seismic facies interpretation based on seismic profiles is a main method for predicting karst reservoirs, namely different seismic waveform characteristics corresponding to different types of reservoirs are summarized according to the reflection characteristic comparison statistical analysis of known wells and seismic channels beside the known wells, and the method is used for predicting the capacity of the karst reservoirs. For example, in 2018, Shoufacusen developed seismic response characteristics and high-yield well seismic mode studies of typical wells of different reservoir combination types by using high-resolution seismic data, and divided the four-section weathering crust karst reservoir into 3 types of seismic modes to qualitatively predict the productivity of the karst reservoir.

However, in the prior art, the energy storage coefficient of the weathered crust karst reservoir is indirectly predicted through parameters such as porosity and thickness, or the productivity of the weathered crust karst reservoir is qualitatively predicted, so that the prediction accuracy of the energy storage coefficient of the weathered crust karst reservoir is not high.

Disclosure of Invention

The embodiment of the invention provides an energy storage coefficient prediction method of a weathering crust karst reservoir, which is used for directly realizing the energy storage coefficient prediction of the weathering crust karst reservoir and improving the energy storage coefficient prediction precision, and the energy storage coefficient prediction method of the weathering crust karst reservoir comprises the following steps:

extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted;

and predicting and obtaining the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

The embodiment of the invention also provides an energy storage coefficient prediction device of the weathering crust karst reservoir, which is used for directly realizing the energy storage coefficient prediction of the weathering crust karst reservoir and improving the energy storage coefficient prediction precision, and the energy storage coefficient prediction device of the weathering crust karst reservoir comprises:

the amplitude attribute extraction module is used for extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted;

and the energy storage coefficient prediction module is used for predicting and obtaining the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the energy storage coefficient prediction method of the weathering crust karst reservoir when executing the computer program.

Embodiments of the present invention further provide a computer-readable storage medium storing a computer program for executing the energy storage coefficient prediction method for a reservoir of a weathering crust karst.

In the embodiment of the invention, the energy storage coefficient of the reservoir to be predicted is obtained by extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted and predicting by utilizing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the embodiment of the invention, the energy storage coefficient of the weathering crust karst reservoir can be directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the prediction precision of the energy storage coefficient of the weathering crust karst reservoir can be improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

fig. 1 is a flow chart of an implementation of a method for predicting an energy storage coefficient of a weathered crust karst reservoir according to an embodiment of the present invention;

fig. 2 is a flowchart of another implementation of the method for predicting the energy storage coefficient of the weathered crust karst reservoir according to the embodiment of the present invention;

FIG. 3 is a flow chart of an implementation of fitting a conversion relationship between an energy storage coefficient and a seismic amplitude attribute value in the method for predicting an energy storage coefficient of a weathered crust karst reservoir provided by the embodiment of the invention;

FIG. 3-1 is a schematic diagram of a three-dimensional forward seismic recording of a target sample reservoir provided by an embodiment of the invention;

FIG. 3-2 is a schematic view of a scatter plot of a target sample reservoir energy storage coefficient and a seismic amplitude attribute value provided by an embodiment of the present invention;

fig. 4 is another flow chart of implementation of fitting a conversion relationship between an energy storage coefficient and a seismic amplitude attribute value in the method for predicting an energy storage coefficient of a weathered crust karst reservoir provided in the embodiment of the present invention;

FIG. 4-1 is a schematic diagram of a three-dimensional forward seismic record after a target sample reservoir is unshielded according to an embodiment of the invention;

fig. 5 is a flowchart illustrating implementation of step 301 in a method for predicting an energy storage coefficient of a weathered crust karst reservoir according to an embodiment of the present invention;

fig. 6 is a flowchart illustrating implementation of step 503 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir according to the embodiment of the present invention;

FIG. 6-1 is a schematic diagram of a three-dimensional wave impedance model of a target sample reservoir provided by an embodiment of the invention;

fig. 7 is a flowchart of another implementation of step 503 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir according to the embodiment of the present invention;

fig. 8 is a flowchart illustrating implementation of step 302 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir according to the embodiment of the present invention;

fig. 9 is a functional block diagram of an energy storage coefficient prediction apparatus for a weathered crust karst reservoir according to an embodiment of the present invention;

fig. 10 is another functional block diagram of an energy storage coefficient prediction apparatus for a weathered crust karst reservoir according to an embodiment of the present invention;

fig. 11 is a structural block diagram of a conversion relationship between a fitting energy storage coefficient and a seismic amplitude attribute value in the energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided in the embodiment of the present invention;

fig. 12 is another structural block diagram of a conversion relationship between fitting energy storage coefficients and seismic amplitude attribute values in the energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided in the embodiment of the present invention;

fig. 13 is a block diagram illustrating a structure of a seismic recording determining module 1101 in the energy storage coefficient prediction apparatus for a weathered crust karst reservoir according to an embodiment of the present invention;

fig. 14 is a structural block diagram of a model building unit 1303 in the device for predicting the energy storage coefficient of a weathered crust karst reservoir according to the embodiment of the present invention;

fig. 15 is another structural block diagram of the model building unit 1303 in the device for predicting the energy storage coefficient of a weathered crust karst reservoir according to the embodiment of the present invention;

fig. 16 is a structural block diagram of a sample seismic amplitude extraction module 1102 in the device for predicting the energy storage coefficient of a weathered crust karst reservoir provided in the embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.

Fig. 1 shows an implementation flow of the method for predicting the energy storage coefficient of a weathered crust karst reservoir provided by an embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

as shown in FIG. 1, the method for predicting the energy storage coefficient of the weathering crust karst reservoir comprises the following steps:

step 101, extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted;

and step 102, predicting and obtaining the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

The non-integrated surface of the weathering crust is preferably deposited for a longer period of time and the erosion is relatively strong. The synbiotic or quasi-synbiotic karst effect caused by short periodic exposure is difficult to form karst with large influence depth, large scale and wide distribution, and is not enough to form karst unconformity, the thickness of a karst reservoir is small, and earthquake identification is difficult.

The embodiment of the invention is described by taking the karst reservoir (namely the target sample reservoir) of the epicentral-Dynasty lamp shadow group in the middle of Sichuan basin as an example. The lamp shade group is lifted under the influence of the movement of the tung bay and is subjected to two-stage atmospheric fresh water leaching transformation with different degrees, and two sets of weathered shell karst reservoirs of the four-stage lamp and the two-stage lamp are formed. In the early stage of early Han Wu dynasty, on the basis of the rugged ancient landform, black gray carbonaceous shale and silty shale of a lower Han WutongZhugang Temple group are deposited, and a Han system and an underlying seismic denier system are in an unconformity contact relationship. The top stratum of the lamp shadow group is exposed on the earth surface, and the carbonate stratum is subjected to long-term strong corrosion action through corrosion leaching of atmospheric fresh water to generate a large number of corrosion holes, the physical property of the reservoir is good, and a high-quality weathered crust karst reservoir is formed at the upper section of the lamp.

When the energy storage coefficient of the weathering crust karst reservoir is predicted, firstly, the seismic amplitude attribute value of seismic data of the reservoir to be predicted is extracted. And the reservoir seismic data to be predicted is seismic data to be processed and used in actual production. And after the seismic amplitude attribute value of the seismic data of the reservoir to be predicted is extracted, predicting the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting so as to obtain the energy storage coefficient of the reservoir to be predicted. The conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting reflects the incidence relation between the energy storage coefficient and the seismic amplitude attribute value, namely, under the condition that the seismic amplitude attribute value is known, the energy storage coefficient of the reservoir to be predicted can be obtained through the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

In the embodiment of the invention, the energy storage coefficient of the reservoir to be predicted is obtained by extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted and predicting by utilizing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the embodiment of the invention, the energy storage coefficient of the weathering crust karst reservoir can be directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the prediction precision of the energy storage coefficient of the weathering crust karst reservoir can be improved.

Fig. 2 shows another implementation flow of the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 2, on the basis of the steps of the method shown in fig. 1, the method for predicting the energy storage coefficient of a weathering crust karst reservoir further includes:

step 201, performing strong reflection shielding removal processing on seismic data of a reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after shielding removal;

step 101, extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted, including:

step 202, extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding is removed.

When the thickness of the karst reservoir is small, the reservoir is influenced by the tuning effect of the strong reflection of the weathered crust, the amplitude rule of the bottom of the reservoir is not obvious, and the karst reservoirs with different thicknesses and porosities may respectively correspond to a strong reflection peak, a zero-point weak reflection peak or a trough. The reservoir bottom surface is difficult to track directly through forward seismic recording, and the correlation between seismic reflection energy and reservoir thickness and porosity is poor, so that reservoir prediction is difficult.

Therefore, before the seismic amplitude attribute value of the seismic data of the reservoir to be predicted is extracted, the seismic data of the reservoir to be predicted can be subjected to strong reflection shielding removal processing, and then the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after shielding removal is extracted. The real seismic reflection of the screened karst reservoir is recovered, the bottom surface of the reservoir corresponds to the wave crest reflection, and the larger the thickness of the reservoir is, the stronger the wave crest energy is, and the larger the porosity is, the stronger the wave crest energy is.

The extracting of the seismic amplitude attribute value of the seismic data of the reservoir to be predicted may specifically include: acquiring seismic data of a reservoir to be predicted; acquiring seismic wavelets of a target sample reservoir according to seismic data of the reservoir to be predicted; constructing a three-dimensional wave impedance model of a reservoir to be predicted; and performing seismic forward modeling by using the constructed three-dimensional wave impedance model and seismic wavelets of the reservoir to be predicted to obtain the three-dimensional forward seismic record of the reservoir to be predicted, and further extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the reservoir to be predicted.

In the embodiment of the invention, the seismic data of the reservoir to be predicted are subjected to strong reflection shielding removal processing to obtain the seismic data of the reservoir to be predicted after the shielding is removed, the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding is removed is extracted, and the prediction precision of the energy storage coefficient can be further improved.

Fig. 3 shows a flow of implementing the fitting of the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value in the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 3, the fitting of the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value includes:

step 301, determining a three-dimensional forward seismic record of a target sample reservoir according to seismic data of the target sample reservoir;

step 302, extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a longitudinal measurement line serial number value and a transverse measurement line serial number value corresponding to the seismic amplitude attribute value;

step 303, determining the energy storage coefficient of the target sample reservoir according to the longitudinal measurement line sequence number value and the transverse measurement line sequence number value corresponding to the seismic amplitude attribute value;

and step 304, performing intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting to construct a conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

When fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, firstly acquiring seismic data of a target sample reservoir, for example acquiring seismic data of an karst reservoir of an epicentral-tunic shadow group in the Sichuan basin from an oil field. And further determining the three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir. Fig. 3-1 shows a three-dimensional forward seismic recording of a karst reservoir (target sample reservoir) of a regional epicentral system light shadow group in the sichuan basin provided by an embodiment of the present invention.

And then extracting a seismic amplitude attribute value Amp (i, j) from the three-dimensional forward seismic record of the target sample reservoir, wherein i and j respectively represent a longitudinal line sequence number value and a transverse line sequence number value corresponding to the seismic amplitude attribute value.

After the seismic amplitude attribute value and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value are extracted, the energy storage coefficient of the target sample reservoir is determined by using the following formula based on a geological model of the weathering crust karst reservoir:

wherein the content of the first and second substances,and i and j respectively represent the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value of the target sample reservoir.

After the seismic amplitude attribute value of the three-dimensional forward modeling seismic record of the target sample reservoir and the energy storage coefficient of the target sample reservoir are obtained respectively, intersection analysis is carried out on the energy storage coefficient of the target sample reservoir and the seismic amplitude attribute value, and a scatter intersection graph of the energy storage coefficient and the seismic amplitude attribute value is obtained. Fig. 3-2 shows a scatter cross plot of the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir provided by the embodiment of the present invention, where the X axis is the seismic amplitude attribute value, and the Y axis is the energy storage coefficient, and it can be seen from fig. 3-2 that there is a good linear relationship between the energy storage coefficient and the seismic amplitude attribute value, and accordingly, the scatter cross plot is used to fit the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value, and the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value can be obtained as follows:

wherein the content of the first and second substances,representing the energy storage coefficient, Amp representing the seismic amplitude attribute value, R²The variance is indicated.

In the embodiment of the invention, the three-dimensional forward seismic record of the target sample reservoir is determined according to the seismic data of the target sample reservoir, further extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the longitudinal measuring line serial number value and the transverse measuring line serial number value corresponding to the seismic amplitude attribute value, and finally, intersection analysis is carried out on the energy storage coefficient of the target sample reservoir and the seismic amplitude attribute value, a conversion relation between the energy storage coefficient and the seismic amplitude attribute value is constructed in a fitting mode, the correlation relation between the energy storage coefficient and the seismic amplitude attribute value can be accurately reflected by the conversion relation obtained in the fitting mode, the energy storage coefficient is predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained in the fitting mode, and the prediction precision of the energy storage coefficient can be further improved.

Fig. 4 shows another implementation flow of fitting a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value in the energy storage coefficient prediction method for the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 4, on the basis of the method steps shown in fig. 3, the fitting a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value further includes:

step 401, performing strong reflection shielding removal treatment on the three-dimensional forward seismic record of the target sample reservoir along the weathering crust to obtain the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal;

step 302, extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value, including:

step 402, extracting the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal, and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value.

When the thickness of the karst reservoir is small, the reservoir is influenced by the tuning effect of the strong reflection of the weathered crust, the amplitude rule of the bottom of the reservoir is not obvious, and the karst reservoirs with different thicknesses and porosities may respectively correspond to a strong reflection peak, a zero-point weak reflection peak or a trough. The reservoir bottom surface is difficult to track directly through forward seismic recording, and the correlation between seismic reflection energy and reservoir thickness and porosity is poor, so that reservoir prediction is difficult.

Therefore, before the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir is extracted, the strong reflection shielding processing can be further carried out on the three-dimensional forward seismic record of the target sample reservoir, and then the seismic amplitude attribute value of the three-dimensional forward seismic record after the shielding of the target sample reservoir is extracted.

Fig. 4-1 shows the three-dimensional forward seismic record of the target sample reservoir after being subjected to shielding removal, and as can be seen from fig. 4-1, the true seismic reflection of the rock solution reservoir after being subjected to shielding removal is recovered, the bottom surface of the reservoir corresponds to the peak reflection, and the peak energy is stronger when the reservoir thickness is larger and the peak energy is stronger when the porosity is larger.

In the embodiment of the invention, the three-dimensional forward seismic record of the target sample reservoir is subjected to strong reflection shielding removal processing along the weathering crust to obtain the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal, the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value are extracted, and the strong reflection shielding removal processing can further improve the prediction precision of the energy storage coefficient.

Fig. 5 shows an implementation flow of step 301 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of determining the three-dimensional forward seismic record of the target sample reservoir, as shown in fig. 5, step 301, determining the three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir includes:

step 501, acquiring seismic data of a target sample reservoir;

step 502, acquiring seismic wavelets of a target sample reservoir according to seismic data of the target sample reservoir;

step 503, constructing a three-dimensional wave impedance model of the target sample reservoir about reservoir thickness, reservoir porosity and time;

and step 504, performing seismic forward modeling by using the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelets to obtain three-dimensional forward seismic records of the target sample reservoir.

When determining the three-dimensional forward seismic record of the target sample reservoir, firstly acquiring the seismic data of the target sample reservoir, further extracting the seismic wavelets of the seismic data of the target sample reservoir, and then constructing a three-dimensional wave impedance model of the target sample reservoir, wherein the three-dimensional wave impedance model of the target sample reservoir is a three-dimensional wave impedance model related to the reservoir thickness, the reservoir porosity and the time. After the seismic wavelet and the three-dimensional wave impedance model of the target sample reservoir are obtained respectively, convolution is carried out on the seismic wavelet and the three-dimensional wave impedance model of the target sample reservoir to carry out seismic forward modeling, and a three-dimensional forward seismic record of the target sample reservoir is obtained (namely, fig. 3-1).

In the embodiment of the invention, the seismic data of the target sample reservoir are firstly obtained, the seismic wavelet of the target sample reservoir is further obtained according to the seismic data of the target sample reservoir, then a three-dimensional wave impedance model of the target sample reservoir about reservoir thickness, reservoir porosity and time is constructed, finally the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelet are used for performing seismic forward modeling, and the three-dimensional forward seismic record of the target sample reservoir is obtained.

Fig. 6 shows an implementation flow of step 503 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of constructing the three-dimensional wave impedance model and further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 6, step 503 is to construct a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity, and the time, and includes:

601, obtaining logging data of a target sample reservoir;

step 602, determining the average wave impedance of the overburden and the average wave impedance of the underburden carbonate in the target sample reservoir by using the logging data of the target sample reservoir;

step 603, determining wave impedances corresponding to weathered crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis by using the logging data of the target sample reservoir;

step 604, establishing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time according to the average wave impedance of the overburden formation and the average wave impedance of the underlying carbonate formation in the target sample reservoir and the wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir.

When a three-dimensional wave impedance model of a target sample reservoir is constructed, well logging data of the target sample reservoir, which comprises acoustic time difference, a density curve, reservoir parameters and the like, is obtained.

In the embodiment of the invention, an upper stratum (a cover layer) of a top weathering crust of a target sample reservoir lamp shade group is a lower tumidinoda qiongensis group stratum, and the lower section of the upper stratum is dark gray, black gray mudstone and black carbonaceous shale. The reservoir of karst is under the weathering crust, and the carbonate stratum under the weathering crust (carbonate stratum) is a lamp shadow carbonate stratum, mainly gray and taupe dolostone. The target sample reservoir includes overburden, karst and underburden. And then carrying out statistical analysis by using the logging data of the target sample reservoir, and calculating and determining that the average wave impedance of the clay shale of the lower tumidinoda group of the overlying strata is 10000m/s multiplied by g/cm³And the average wave impedance of carbonate rock under the weathering crust is 13800m/s × g/cm³. Furthermore, the corresponding wave impedance of the weathering crust karst reservoirs with different porosities in the target sample reservoir is calculated by using the logging data of the target sample reservoir and a rock physical analysis method.

After the average wave impedance of an overlying stratum and the average wave impedance of an underlying carbonate stratum in a target sample reservoir and the wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir are respectively obtained, a three-dimensional wave impedance model of the target sample reservoir about the reservoir thickness, the reservoir porosity and the time is established based on the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir and the wave impedances corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir.

FIG. 6-1 illustrates a three-dimensional wave impedance model of a target sample reservoir provided by an embodiment of the present invention, with the inline direction being the reservoir thickness, increasing from 0 to 30 meters step-by-step; the transverse line direction is porosity, and the porosity is changed from 0% to 10%; the Z direction is the time depth and the sampling rate is 1 ms. FIG. 6-1 shows the weathering crust at a time depth of 20ms, a stable thickness of mudstone formation (overburden) above the weathering crust, and a wave impedance of 10000m/s×g/cm³(ii) a A karst reservoir is arranged under the weathering crust, and the wave impedance variation range of the reservoir with the porosity from 0 percent to 10 percent is 10900 to 13800m/s multiplied by g/cm³(ii) a The lowest part is carbonate rock non-reservoir stratum (underburden), and the wave impedance is 13800m/s × g/cm³。

In the embodiment of the invention, the logging data of the target sample reservoir is firstly obtained, the logging data of the target sample reservoir is further utilized to determine the average wave impedance of the overburden stratum and the average wave impedance of the carbonate underlayer stratum in the target sample reservoir, then the logging data of the target sample reservoir is utilized to determine the wave impedance corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis, finally, the three-dimensional wave impedance model of the target sample reservoir related to the reservoir thickness, the reservoir porosity and the time is established according to the average wave impedance of the overburden stratum and the average wave impedance of the carbonate underlayer in the target sample reservoir and the wave impedance corresponding to the weathering crust karst reservoirs with different porosities in the target sample reservoir, and the three-dimensional wave impedance model related to the reservoir thickness, the reservoir porosity and the time is established, so that the accuracy of establishing the three-dimensional wave impedance model can be improved, and further improve the prediction accuracy of the energy storage coefficient.

Fig. 7 shows another implementation flow of step 503 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to further improve the accuracy of constructing the three-dimensional wave impedance model, as shown in fig. 7, on the basis of the method steps shown in fig. 6, step 503 is to construct a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity, and the time, and further includes:

step 701, determining the reservoir thickness maximum value and the porosity maximum value of the weathering crust karst reservoir in the target sample reservoir by using the logging data of the target sample reservoir.

The three-dimensional wave impedance model of the target sample reservoir takes the reservoir thickness change direction as a longitudinal measurement line direction, the reservoir porosity change direction as a transverse measurement line direction, and the time change direction as a vertical measurement line direction;

the reservoir thickness of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum reservoir thickness along the longitudinal measuring line direction, and the porosity of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum porosity along the transverse measuring line direction.

Determining the maximum value h of the thickness of a karst reservoir by utilizing logging data of a target sample reservoir based on regional geological knowledge of the karst reservoir of a weathering crust_maxAnd maximum value of porosity phi_max. The seismic grid of the three-dimensional wave impedance model of the target sample reservoir is set to: the longitudinal measuring line direction is the reservoir thickness variation direction; the transverse measuring line direction is the reservoir porosity change direction; the Z direction is the time direction. And the three-dimensional wave impedance model of the target sample reservoir is a 3-layer wave impedance model from top to bottom along the weathering crust. An overlying formation of stable, uniform thickness over the weathering crust; a karst reservoir is arranged under the weathering crust, and the thickness of the reservoir corresponding to the longitudinal measuring line direction is from 0 to h_maxThe porosity of the reservoir corresponding to the transverse survey line direction is changed from 0 to phi_max(ii) a Below the karst reservoir is a homogeneous carbonate non-reservoir underburden. In the embodiment of the Sichuan basin, the thickness value of the karst reservoir is counted according to the existing actual drilling result of the research area, the maximum value of the thickness of the karst reservoir is determined to be 30 meters, and the maximum porosity is 10 percent.

In the embodiment of the invention, the maximum reservoir thickness value and the maximum porosity value of the weathered crust karst reservoir in the target sample reservoir are determined by utilizing the logging data of the target sample reservoir, so that the accuracy of constructing the three-dimensional wave impedance model can be further improved, and the prediction precision of the energy storage coefficient is further improved.

Fig. 8 shows an implementation flow of step 302 in the method for predicting the energy storage coefficient of the weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of extracting the seismic amplitude attribute value and further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 8, step 302, extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the vertical line serial number value and the horizontal line serial number value corresponding to the seismic amplitude attribute value, includes:

step 801, determining an effective seismic response time window of a target sample reservoir according to a three-dimensional forward seismic record of the target sample reservoir; the effective seismic response time window of the target sample reservoir is the time length of the weathering crust to the bottom of the reservoir corresponding to the wave crest reflection on the seismic channel where the maximum thickness and the maximum porosity of the reservoir are located;

and 802, extracting the seismic amplitude attribute value and a longitudinal measurement line serial number value and a transverse measurement line serial number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

When the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir is extracted, firstly, the effective seismic response time window of the target sample reservoir is determined according to the three-dimensional forward seismic record of the target sample reservoir. The effective seismic response time window of the target sample reservoir is the time length of the weathering crust to the bottom of the reservoir corresponding to the wave crest reflection on the seismic channel where the maximum thickness and the maximum porosity of the reservoir are located. Fig. 4-1 shows the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal, and as can be seen from fig. 4-1, the time ranges corresponding to the seismic wave crest reflections of different karst reservoirs are 20-39 ms, so that the effective seismic response time window of the reservoir is determined to be from the weathering crust to the weathering crust for 19ms downwards.

And after the effective seismic response time window of the target sample reservoir is determined, extracting a seismic amplitude attribute value Amp (i, j) along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir. Wherein, i and j respectively represent the longitudinal survey line serial number value and the transverse survey line serial number value corresponding to the seismic amplitude attribute value.

In the embodiment of the invention, the effective seismic response time window of the target sample reservoir is determined according to the three-dimensional forward seismic record of the target sample reservoir, the seismic amplitude attribute value and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value are extracted along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir, and the seismic amplitude attribute value is extracted along the effective seismic response time window, so that the accuracy of extracting the seismic amplitude attribute value can be improved, and the prediction precision of the energy storage coefficient is further improved.

The embodiment of the invention also provides an energy storage coefficient prediction device of the weathering crust karst reservoir, which is described in the following embodiment. Because the principle of solving the problems of the devices is similar to the energy storage coefficient prediction method of the weathering crust karst reservoir, the implementation of the devices can be referred to the implementation of the method, and repeated details are not repeated.

Fig. 9 shows functional modules of an energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided by an embodiment of the present invention, and for convenience of explanation, only parts related to the embodiment of the present invention are shown, and detailed description is as follows:

referring to fig. 9, the energy storage coefficient prediction apparatus for a weathering crust karst reservoir includes modules for performing the steps in the embodiment corresponding to fig. 1, and specific reference is made to fig. 1 and the related description in the embodiment corresponding to fig. 1, which are not repeated herein. In the embodiment of the invention, the energy storage coefficient prediction device for the weathered crust karst reservoir comprises an amplitude attribute extraction module 901 and an energy storage coefficient prediction module 902.

The amplitude attribute extraction module 901 is configured to extract a seismic amplitude attribute value of seismic data of a reservoir to be predicted.

And the energy storage coefficient prediction module 902 is configured to predict and obtain the energy storage coefficient of the reservoir to be predicted by using the conversion relationship between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value.

In the embodiment of the invention, the amplitude attribute extraction module 901 extracts the seismic amplitude attribute value of the seismic data of the reservoir to be predicted, and the energy storage coefficient prediction module 902 predicts and obtains the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the embodiment of the invention, the energy storage coefficient of the weathering crust karst reservoir can be directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the prediction precision of the energy storage coefficient of the weathering crust karst reservoir can be improved.

Fig. 10 shows another functional block of the energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided by an embodiment of the present invention, and for convenience of explanation, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 10, each unit included in the energy storage coefficient prediction apparatus for a reservoir of a weathering crust karst is configured to perform each step in the embodiment corresponding to fig. 2, and specific reference is made to fig. 2 and the related description in the embodiment corresponding to fig. 2, which is not repeated herein. In the embodiment of the present invention, on the basis of the functional module shown in fig. 9, the apparatus for predicting the energy storage coefficient of a reservoir of a weathering crust karst further includes a shielding removal processing module 1001.

And the unshielding processing module 1001 is used for carrying out unshielding reflection shielding processing on the seismic data of the reservoir to be predicted to obtain the unshielded seismic data of the reservoir to be predicted.

The amplitude attribute extraction module 901 is further configured to extract a seismic amplitude attribute value of the seismic data after the reservoir to be predicted is unshielded.

In the embodiment of the present invention, the unshielding processing module 1001 performs unshielding processing on the seismic data of the reservoir to be predicted to obtain the unshielded seismic data of the reservoir to be predicted, and the amplitude attribute extracting module 901 extracts the seismic amplitude attribute value of the unshielded seismic data of the reservoir to be predicted, which can further improve the prediction accuracy of the energy storage coefficient.

Fig. 11 is a schematic structural diagram illustrating a conversion relationship between fitting energy storage coefficients and seismic amplitude attribute values in an energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided by an embodiment of the present invention, and for convenience of explanation, only the parts related to the embodiment of the present invention are shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 11, each unit included in the conversion relationship between the fitting energy storage coefficient and the seismic amplitude attribute value is used to perform each step in the embodiment corresponding to fig. 3, and specifically refer to fig. 3 and the description related to the embodiment corresponding to fig. 3, which is not repeated herein. In the embodiment of the present invention, the conversion relationship between the fitting energy storage coefficient and the seismic amplitude attribute value includes a seismic record determining module 1101, a sample seismic amplitude extracting module 1102, a sample energy storage coefficient determining module 1103, and a conversion relationship fitting constructing module 1104.

The seismic record determining module 1101 is configured to determine a three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir.

The sample seismic amplitude extraction module 1102 is configured to extract a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a longitudinal measurement line serial number value and a transverse measurement line serial number value corresponding to the seismic amplitude attribute value.

And the sample energy storage coefficient determining module 1103 is configured to determine the energy storage coefficient of the target sample reservoir according to the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value.

And the conversion relation fitting construction module 1104 is used for performing intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting and constructing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

In the embodiment of the invention, the seismic record determining module 1101 determines the three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir, the sample seismic amplitude extracting module 1102 extracts the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value, the sample energy storage coefficient determining module 1103 determines the energy storage coefficient of the target sample reservoir according to the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value, finally the conversion relation fitting and constructing module 1104 performs intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, the conversion relation between the energy storage coefficient and the seismic amplitude attribute value is constructed by fitting, and the conversion relation obtained by fitting can accurately reflect the association relation between the energy storage coefficient and the seismic amplitude attribute value, the energy storage coefficient is predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained by fitting, and the prediction precision of the energy storage coefficient can be further improved.

Fig. 12 shows another structural schematic diagram of the energy storage coefficient prediction apparatus for a weathered crust karst reservoir, which is provided by the embodiment of the present invention, and shows only the part related to the embodiment of the present invention for convenience of explanation, and the detailed description is as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 12, each unit included in the conversion relationship between the fitting energy storage coefficient and the seismic amplitude attribute value is used to execute each step in the embodiment corresponding to fig. 4, and specific reference is made to fig. 4 and the description in the embodiment corresponding to fig. 4, which is not repeated herein. In the embodiment of the present invention, based on the module structure shown in fig. 11, the fitting module further includes a sample unshielding processing module 1201 according to the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value.

And the sample de-shielding processing module 1201 is used for performing strong reflection shielding processing on the three-dimensional forward seismic record of the target sample reservoir along the weathering crust to obtain the de-shielded three-dimensional forward seismic record of the target sample reservoir.

The sample seismic amplitude extraction module 1102 is further configured to extract a seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding removal, and a longitudinal measurement line serial number value and a transverse measurement line serial number value corresponding to the seismic amplitude attribute value.

In the embodiment of the invention, the sample de-shielding processing module 1201 performs de-strong reflection shielding processing on the three-dimensional forward seismic record of the target sample reservoir along the weathering crust to obtain the de-shielded three-dimensional forward seismic record of the target sample reservoir, the sample seismic amplitude extraction module 1102 extracts the seismic amplitude attribute value of the de-shielded three-dimensional forward seismic record of the target sample reservoir and the longitudinal measurement line serial number value and the transverse measurement line serial number value corresponding to the seismic amplitude attribute value, and the de-strong reflection shielding processing can further improve the prediction precision of the energy storage coefficient.

Fig. 13 shows a structural schematic diagram of a seismic recording determination module 1101 in the energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of explanation, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of determining the target sample reservoir three-dimensional forward seismic record, referring to fig. 13, each unit included in the seismic record determining module 1101 is configured to execute each step in the embodiment corresponding to fig. 5, specifically please refer to fig. 5 and the related description in the embodiment corresponding to fig. 5, which is not repeated herein. In the embodiment of the present invention, the seismic record determining module 1101 includes a seismic data obtaining unit 1301, a wavelet obtaining unit 1302, a model building unit 1303, and a forward modeling unit 1304.

The seismic data acquisition unit 1301 is used for acquiring seismic data of a target sample reservoir.

The wavelet obtaining unit 1302 is configured to obtain a seismic wavelet of a target sample reservoir according to seismic data of the target sample reservoir.

And the model building unit 1303 is used for building a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time.

And the forward modeling unit 1304 is used for performing seismic forward modeling by using the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelets to obtain a three-dimensional forward seismic record of the target sample reservoir.

In the embodiment of the invention, firstly, the seismic data acquisition unit 1301 acquires seismic data of a target sample reservoir, then the wavelet acquisition unit 1302 acquires seismic wavelets of the target sample reservoir according to the seismic data of the target sample reservoir, then the model construction unit 1303 constructs a three-dimensional wave impedance model of the target sample reservoir about reservoir thickness, reservoir porosity and time, and finally the forward modeling unit 1304 performs seismic forward modeling by using the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelets to acquire a three-dimensional forward seismic record of the target sample reservoir.

Fig. 14 shows a structural schematic diagram of a model building unit 1303 in the device for predicting the energy storage coefficient of a weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of description, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of constructing the three-dimensional wave impedance model and further improve the prediction accuracy of the energy storage coefficient, referring to fig. 14, each unit included in the model constructing unit 1303 is configured to perform each step in the embodiment corresponding to fig. 6, specifically refer to fig. 6 and the related description in the embodiment corresponding to fig. 6, and details are not repeated here. In the embodiment of the present invention, the model building unit 1303 includes a logging data obtaining subunit 1401, an upper and lower formation wave impedance determining subunit 1402, a karst reservoir wave impedance determining subunit 1403, and a model building subunit 1404.

And a logging data acquiring subunit 1401, configured to acquire logging data of the target sample reservoir.

The upper and lower formation wave impedance determination subunit 1402 is configured to determine an average wave impedance of an overburden formation and an average wave impedance of an underburden carbonate formation in the target sample reservoir using the well logging data of the target sample reservoir.

The karst reservoir wave impedance determination subunit 1403 is configured to determine, through petrophysical analysis, wave impedances corresponding to the weathering crust karst reservoirs of different porosities in the target sample reservoir by using the well logging data of the target sample reservoir.

The model building subunit 1404 is configured to build a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity, and time according to the average wave impedance of the overlying strata and the average wave impedance of the underlying carbonate strata in the target sample reservoir, and the wave impedances corresponding to the weathering crust karst reservoirs of different porosities in the target sample reservoir.

In the embodiment of the present invention, firstly, the logging data obtaining subunit 1401 obtains logging data of a target sample reservoir, then the upper and lower formation wave impedance determining subunit 1402 determines the average wave impedance of an overlying formation and the average wave impedance of an underlying carbonate formation in the target sample reservoir by using the logging data of the target sample reservoir, then the karst reservoir wave impedance determining subunit 1403 determines the wave impedances corresponding to the weathered crust karst reservoirs with different porosities in the target sample reservoir by using the logging data of the target sample reservoir through petrophysical analysis, finally, the model building subunit 1404 builds a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overlying formation and the average wave impedance of the underlying carbonate formation in the target sample reservoir and the wave impedances corresponding to the weathered crust karst reservoirs with different porosities in the target sample reservoir, by constructing the three-dimensional wave impedance model related to the thickness of the reservoir, the porosity of the reservoir and the time, the accuracy of constructing the three-dimensional wave impedance model can be improved, and the prediction precision of the energy storage coefficient is further improved.

Fig. 15 shows another structural schematic diagram of the model building unit 1303 in the device for predicting the energy storage coefficient of a weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of explanation, only the parts related to the embodiment of the present invention are shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the accuracy of constructing the three-dimensional wave impedance model, referring to fig. 15, each unit included in the model constructing unit 1303 is configured to perform each step in the embodiment corresponding to fig. 7, and specifically, refer to fig. 7 and the description related to the embodiment corresponding to fig. 7, which is not repeated herein. In the embodiment of the present invention, on the basis of the module structure shown in fig. 14, the model building unit 1303 further includes a maximum value determining subunit 1501.

The maximum value determining subunit 1501 is configured to determine, by using the well logging data of the target sample reservoir, a reservoir thickness maximum value and a porosity maximum value of the weathering crust karst reservoir in the target sample reservoir.

The three-dimensional wave impedance model of the target sample reservoir takes the reservoir thickness change direction as a longitudinal measurement line direction, the reservoir porosity change direction as a transverse measurement line direction, and the time change direction as a vertical measurement line direction;

the reservoir thickness of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum reservoir thickness along the longitudinal measuring line direction, and the porosity of the weathering crust karst reservoir in the target sample reservoir is gradually changed from zero to the maximum porosity along the transverse measuring line direction.

In the embodiment of the present invention, the maximum value determining subunit 1501 determines the maximum reservoir thickness value and the maximum porosity value of the weathering crust karst reservoir in the target sample reservoir by using the logging data of the target sample reservoir, so as to further improve the accuracy of constructing the three-dimensional wave impedance model, and further improve the prediction accuracy of the energy storage coefficient.

Fig. 16 shows a structural schematic diagram of a sample seismic amplitude extraction module 1102 in the energy storage coefficient prediction apparatus for a weathered crust karst reservoir provided by the embodiment of the present invention, and for convenience of explanation, only the part related to the embodiment of the present invention is shown, and the detailed description is as follows:

in an embodiment of the present invention, in order to improve the accuracy of extracting the seismic amplitude attribute value, referring to fig. 16, each unit included in the sample seismic amplitude extraction module 1102 is configured to execute each step in the embodiment corresponding to fig. 8, specifically please refer to fig. 8 and the description related to the embodiment corresponding to fig. 8, which is not repeated herein. In the embodiment of the present invention, the sample seismic amplitude extraction module 1102 includes a response time window determination unit 1601 and a seismic amplitude attribute extraction unit 1602.

The response time window determining unit 1601 is used for determining an effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective seismic response time window of the target sample reservoir is the time length of the weathering crust to the bottom of the reservoir corresponding to the wave crest reflection on the seismic channel where the maximum thickness and the maximum porosity of the reservoir are located.

The seismic amplitude attribute extraction unit 1602 is configured to extract the seismic amplitude attribute value and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

In the embodiment of the present invention, the response time window determining unit 1601 is configured to determine an effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir, and then the seismic amplitude attribute extracting unit 1602 is configured to extract the seismic amplitude attribute value and the vertical measurement line serial number value and the horizontal measurement line serial number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir, and extract the seismic amplitude attribute value along the effective seismic response time window, so that accuracy of extracting the seismic amplitude attribute value can be improved, and prediction accuracy of the energy storage coefficient can be further improved.

Compared with a method for indirectly predicting the energy production (energy storage coefficient) of the karst reservoir by equal ancient landform restoration and earthquake, the embodiment of the invention utilizes logging data and seismic data, and analyzes the intrinsic quantitative relation among the thickness, the porosity and the earthquake of the karst reservoir from a mechanism by establishing a karst reservoir three-dimensional wave impedance model with continuously changed thickness and porosity and forward seismic record analysis thereof, thereby directly realizing the quantitative prediction of the energy storage coefficient of the weathering crust karst reservoir.

The existing seismic prediction method of the energy storage coefficient respectively predicts the porosity and the thickness of a reservoir by adopting seismic data, and then multiplies the porosity and the thickness to obtain the energy storage coefficient. The embodiment of the invention directly realizes the prediction of the energy storage coefficient of the karst reservoir, and the productivity prediction precision is higher. The method is particularly represented in three aspects: firstly, two main key factors influencing the capacity of a karst reservoir are considered at the same time: thickness and porosity; secondly, an internal quantitative relation among the thickness, the porosity and the seismic amplitude attribute is established, the seismic attribute is endowed with reasonable physical significance, and seismic information is more fully applied; thirdly, the real seismic reflection of the karst reservoir is recovered by adopting strong reflection shielding treatment along the weathering crust, and the weak reflection characteristic of the reservoir is recovered and highlighted so as to better improve the prediction capability.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the energy storage coefficient prediction method of the weathering crust karst reservoir when executing the computer program.

Embodiments of the present invention further provide a computer-readable storage medium storing a computer program for executing the energy storage coefficient prediction method for a reservoir of a weathering crust karst.

In summary, in the embodiment of the present invention, the energy storage coefficient of the reservoir to be predicted is obtained by extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted, and predicting by using the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the embodiment of the invention, the energy storage coefficient of the weathering crust karst reservoir can be directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the prediction precision of the energy storage coefficient of the weathering crust karst reservoir can be improved.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.