阅读说明：本技术 缝洞储层反演方法及系统 (Fracture-cave reservoir inversion method and system ) 是由 陈冬 于 2019-08-23 设计创作，主要内容包括：公开了一种缝洞储层反演方法及系统。该方法包括：步骤1：获得预处理后的测井数据；步骤2：根据叠后地震数据与预处理后的测井数据,获得井旁道地震子波；步骤3：根据预处理后的测井资料、叠后地震数据与井旁道地震子波,建立低频模型；步骤4：针对低频模型进行迭代修正,获得叠后波阻抗反演阻抗体；步骤5：确定叠后地质统计学反演相关参数；步骤6：获得叠后反演波阻抗残差体；步骤7：获得最终的叠后波阻抗反演阻抗体。本发明通过误差迭代法得到波阻抗反演结果,根据高精度波阻抗残差体对波阻抗体进行回校得到高精度反演结果,缝洞储集体有利储层分布平面图与实际钻井生产情况吻合度更高,提高了缝洞储层地震反演的精度。(A fracture-cave reservoir inversion method and system are disclosed. The method comprises the following steps: step 1: obtaining pre-processed logging data; step 2: acquiring well side channel seismic wavelets according to the post-stack seismic data and the preprocessed logging data; and step 3: establishing a low-frequency model according to the preprocessed logging data, the post-stack seismic data and the well side channel seismic wavelets; and 4, step 4: performing iterative correction on the low-frequency model to obtain a post-stack wave impedance inversion impedance body; and 5: determining relevant parameters of post-stack geostatistical inversion; step 6: obtaining a post-stack inversion wave impedance residual error body; and 7: and obtaining a final post-stack wave impedance inversion impedance body. According to the method, the wave impedance inversion result is obtained through an error iteration method, the wave impedance body is subjected to back correction according to the high-precision wave impedance residual error body to obtain the high-precision inversion result, the goodness of fit between the fracture-cave reservoir favorable reservoir distribution plane diagram and the actual drilling production condition is higher, and the precision of fracture-cave reservoir seismic inversion is improved.)

1. A fracture-cavity reservoir inversion method is characterized by comprising the following steps:

step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data;

step 2: extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets;

and step 3: establishing a low-frequency model according to the preprocessed logging information, the post-stack seismic data and the well side channel seismic wavelets;

and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body;

and 5: determining post-stack geostatistical inversion related parameters according to geological knowledge, the post-stack wave impedance inversion impedance body and the preprocessed logging data;

step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to the post-stack geostatistical inversion related parameters to obtain a post-stack inversion wave impedance residual error body;

and 7: and performing error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

2. A fracture-cavity reservoir inversion method as defined in claim 1, wherein said step 4 further comprises:

carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body;

and extracting the impedance at the well point and the impedance on the well according to the post-stack wave impedance body, and performing residual comparison calculation to obtain the wave impedance residual body.

3. A fracture-cavity reservoir inversion method as defined in claim 2, wherein said iteratively modifying of step 4 for said low-frequency model comprises:

step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of a seismic data item to obtain a corrected low-frequency model;

step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model;

step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as the post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as the low-frequency model, and repeating the steps 401 and 403.

4. A fracture cavity reservoir inversion method as defined in claim 3, wherein said step 403 further comprises:

calculating the wave impedance of an original well point according to the preprocessed logging data;

and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

5. A fracture-cavity reservoir inversion method as defined in claim 1, wherein the preprocessing of step 1 comprises: borehole collapse correction, multi-well standardization and consistency processing.

6. A fracture-cave reservoir inversion system, comprising:

a memory storing computer-executable instructions;

a processor executing computer executable instructions in the memory to perform the steps of:

step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data;

step 2: extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets;

and step 3: establishing a low-frequency model according to the preprocessed logging information, the post-stack seismic data and the well side channel seismic wavelets;

and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body;

and 5: determining post-stack geostatistical inversion related parameters according to geological knowledge, the post-stack wave impedance inversion impedance body and the preprocessed logging data;

step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to the post-stack geostatistical inversion related parameters to obtain a post-stack inversion wave impedance residual error body;

and 7: and performing error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

7. A fracture cavity reservoir inversion system as defined in claim 6, wherein said step 4 further comprises:

carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body;

and extracting the impedance at the well point and the impedance on the well according to the post-stack wave impedance body, and performing residual comparison calculation to obtain the wave impedance residual body.

8. A fracture-cavern reservoir inversion system as recited in claim 7, wherein the iterative modification of the low-frequency model of step 4 comprises:

step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of a seismic data item to obtain a corrected low-frequency model;

step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model;

step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as the post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as the low-frequency model, and repeating the steps 401 and 403.

9. A fracture cavity reservoir inversion system as defined in claim 8, wherein the step 403 further comprises:

calculating the wave impedance of an original well point according to the preprocessed logging data;

and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

10. A fracture-cavern reservoir inversion system as recited in claim 6, wherein the preprocessing of step 1 comprises: borehole collapse correction, multi-well standardization and consistency processing.

Technical Field

The invention relates to the field of oil and gas seismic exploration and development, in particular to a fracture-cave reservoir inversion method and system.

Background

With the continuous deepening of oil and gas exploration, the continuous discovery of large marine-phase oil and gas fields in the south and the west, carbonate rock fracture-cave oil and gas reservoirs become important targets of oil and gas exploration in China, and the comprehensive prediction of fracture-cave reservoirs becomes a research focus of more and more attention of geophysicists.

Compared with a clastic rock reservoir, the carbonate reservoir has the characteristics of strong heterogeneity, severe transverse change and changeable reservoir space. Seismic inversion is an effective means for (semi-) quantitative prediction of fracture-cavity reservoirs, and wave impedance parameters are used as links for linking seismic, well logging and geological information and are indispensable contents for reservoir prediction. The existing fracture-cavity carbonate reservoir seismic inversion method comprises deterministic wave impedance data volume inversion and the like and geostatistical inversion based on random simulation.

The conventional wave impedance inversion of the fracture-cavity reservoir has the problems of insufficient resolution and multi-solution of the result. The geostatistical inversion can give consideration to the seismic transverse resolution and the logging longitudinal resolution, and integrates the advantages of seismic inversion and reservoir random modeling. The method has obvious advantages in characterization of the fracture-cavity reservoir. However, the stochastic simulation is inherently based on well point interpolation for the prediction of the lateral spread of the reservoir, and depends to a large extent on the number of wells in the work area and the spatial distribution rule. For the stratum with strong heterogeneity such as carbonate rock, the underground geologic body does not have obvious layering, the logging only reflects the stratum information near the borehole, and the leakage and emptying of drilling fluid are easy to occur in the drilling process, so that the logging curve is lost or distorted. In addition, the method is completely based on the assumption of statistics, and black box inversion is carried out, so that the reliability of reservoir prediction is low, the physical significance is not clear, the theoretical basis of transverse extrapolation is lacked, and the method is completely based on data inversion.

In the prior art, aiming at the defect of low wave impedance inversion resolution, the probability density distribution function of a carbonate reservoir to be predicted is obtained from logging data statistics to complete iterative well-free constraint inversion, but the following problems exist: firstly, a geostatistical well interpolation algorithm causes that the horizontal layering of an inversion result is serious, and a carbonate rock fracture-cave reservoir layer does not have obvious layering; logging only reflects stratum information near a well bore, and drilling fluid leakage and emptying are easy to occur in the drilling process, so that a logging curve is lost or distorted. Thereby leading to an increase in uncertainty or spurious of the inversion result; and thirdly, the whole seismic data is inverted by adopting a geostatistical inversion method, so that the calculation amount is large, and the time is long. Therefore, there is a need to develop a fracture-cavity reservoir inversion method and system.

The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

Disclosure of Invention

The invention provides a fracture-cavity reservoir inversion method and a fracture-cavity reservoir inversion system, which can obtain a wave impedance inversion result through an error iteration method, and perform back correction on a wave impedance body according to a high-precision wave impedance residual error body to obtain a high-precision inversion result.

According to one aspect of the invention, a fracture-cave reservoir inversion method is provided. The method may include: step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data; step 2: extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets; and step 3: establishing a low-frequency model according to the preprocessed logging information, the post-stack seismic data and the well side channel seismic wavelets; and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; and 5: determining post-stack geostatistical inversion related parameters according to geological knowledge, the post-stack wave impedance inversion impedance body and the preprocessed logging data; step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to the post-stack geostatistical inversion related parameters to obtain a post-stack inversion wave impedance residual error body; and 7: and performing error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

Preferably, the step 4 further comprises: carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body; and extracting the impedance at the well point and the impedance on the well according to the post-stack wave impedance body, and performing residual comparison calculation to obtain the wave impedance residual body.

Preferably, the iteratively modifying the low-frequency model in step 4 includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of a seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as the post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as the low-frequency model, and repeating the steps 401 and 403.

Preferably, the step 403 further comprises: calculating the wave impedance of an original well point according to the preprocessed logging data; and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

Preferably, the pretreatment of step 1 comprises: borehole collapse correction, multi-well standardization and consistency processing.

According to another aspect of the invention, a fracture-cave reservoir inversion system is provided, which is characterized by comprising: a memory storing computer-executable instructions; a processor executing computer executable instructions in the memory to perform the steps of: step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data; step 2: extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets; and step 3: establishing a low-frequency model according to the preprocessed logging information, the post-stack seismic data and the well side channel seismic wavelets; and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; and 5: determining post-stack geostatistical inversion related parameters according to geological knowledge, the post-stack wave impedance inversion impedance body and the preprocessed logging data; step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to the post-stack geostatistical inversion related parameters to obtain a post-stack inversion wave impedance residual error body; and 7: and performing error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

Preferably, the step 4 further comprises: carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body; and extracting the impedance at the well point and the impedance on the well according to the post-stack wave impedance body, and performing residual comparison calculation to obtain the wave impedance residual body.

Preferably, the iteratively modifying the low-frequency model in step 4 includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of a seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as the post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as the low-frequency model, and repeating the steps 401 and 403.

Preferably, the step 403 further comprises: calculating the wave impedance of an original well point according to the preprocessed logging data; and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

Preferably, the pretreatment of step 1 comprises: borehole collapse correction, multi-well standardization and consistency processing.

The method and apparatus of the present invention have other features and advantages which will be apparent from or are set forth in detail in the accompanying drawings and the following detailed description, which are incorporated herein, and which together serve to explain certain principles of the invention.

Drawings

The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts.

FIG. 1 shows a flow chart of the steps of a method of fracture-cavity reservoir inversion according to the present invention.

FIG. 2 illustrates a cross-sectional view of a final post-stack wave impedance inversion impedance volume according to one embodiment of the invention.

Detailed Description

The invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

FIG. 1 shows a flow chart of the steps of a method of fracture-cavity reservoir inversion according to the present invention.

In this embodiment, the fracture-cavity reservoir inversion method according to the present invention may include: step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data; step 2: extracting well-passing seismic channels according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the pre-processed logging data to obtain well side channel seismic wavelets; and step 3: establishing a low-frequency model according to the preprocessed logging data, the post-stack seismic data and the well side channel seismic wavelets; and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; and 5: according to geological knowledge, a post-stack wave impedance inversion impedance body and the preprocessed logging data, determining post-stack geostatistical inversion related parameters; step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to post-stack geostatistical inversion related parameters to obtain a post-stack inverted wave impedance residual error body; and 7: and carrying out error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

In one example, step 4 further comprises: carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body; and extracting impedance at the well point and performing residual comparison calculation on the impedance on the well according to the post-stack wave impedance body to obtain a wave impedance residual body.

In one example, the iteratively modifying for the low frequency model of step 4 includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of the seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as a post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as a low-frequency model, and repeating the steps 401 and 403.

In one example, step 403 further comprises: calculating the wave impedance of an original well point according to the preprocessed logging data; and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

In one example, the preprocessing of step 1 includes: borehole collapse correction, multi-well standardization and consistency processing.

Specifically, the fracture-cavity reservoir inversion method according to the invention can comprise the following steps:

step 1: and carrying out preprocessing such as borehole collapse correction, multi-well standardization and consistency processing on the logging data of the area to be predicted to obtain the preprocessed logging data.

Step 2: and extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets.

And step 3: and establishing a low-frequency model according to the preprocessed logging data, the post-stack seismic data and the well side channel seismic wavelets.

And 4, step 4: carrying out constraint development deterministic inversion on well side channel seismic wavelets and a low-frequency model, adjusting and determining inversion parameters including the sampling rate of selected logging data, the sampling interval of longitudinal time and depth domain of the seismic data, Gardner formula coefficients, high and low frequency cutoff frequency, hard constraint trend, signal-to-noise ratio numerical values and the like according to the signal-to-noise ratio of seismic data and preprocessed logging data, and finally determining various parameter values by repeatedly adjusting the parameter values and comparing inversion test results to further generate a post-stack wave impedance body; extracting impedance at a well point and performing residual comparison calculation on the impedance at the well point and the impedance on the well according to the post-stack wave impedance body to obtain a wave impedance residual body;

according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; the iterative modification of the low-frequency model specifically includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of the seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: calculating original well point wave impedance according to the preprocessed well logging data, calculating a difference value between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error, judging whether the well point error of the corrected post-stack wave impedance body meets a set requirement, if so, taking the corrected post-stack wave impedance body as a post-stack wave impedance inversion impedance body, if not, taking the corrected low-frequency model as a low-frequency model, and repeating the steps 401 and 403.

And 5: determining relevant parameters of post-stack geostatistical inversion according to geological knowledge, post-stack wave impedance inversion impedance bodies and preprocessed logging data, wherein the relevant parameters comprise an xyz three-way variable range value, a base station value, a lump metal effect value, a sand-shale ratio and a geologic body strike angle of a variation function, and also comprise a probability distribution density function, a selection of a variation function fitting algorithm and the like.

Step 6: and taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to post-stack geostatistical inversion related parameters to obtain a post-stack inverted wave impedance residual error body.

And 7: and adding the post-stack inverted wave impedance residual error body and the post-stack wave impedance inverted impedance body for error correction to obtain a final post-stack wave impedance inverted impedance body for inversion of the fracture-cave reservoir stratum.

According to the method, a wave impedance inversion result is obtained through an error iteration method, the wave impedance body is subjected to back correction according to the high-precision wave impedance residual error body to obtain a high-precision inversion result, the goodness of fit between a distributed planar graph of the favorable reservoir of the fracture-cave reservoir and the actual drilling production condition is higher, and the precision of seismic inversion of the fracture-cave reservoir is improved.

Application example

To facilitate understanding of the solution of the embodiments of the present invention and the effects thereof, a specific application example is given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.

The method for inverting the fracture-cavity reservoir comprises the following steps:

step 1: and carrying out preprocessing such as borehole collapse correction, multi-well standardization and consistency processing on the logging data of the area to be predicted to obtain the preprocessed logging data.

Step 2: and extracting well-passing seismic traces according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the preprocessed logging data to obtain well side-channel seismic wavelets.

And step 3: and establishing a low-frequency model according to the preprocessed logging data, the post-stack seismic data and the well side channel seismic wavelets.

And 4, step 4: carrying out constraint development deterministic inversion on well side channel seismic wavelets and a low-frequency model, adjusting and determining inversion parameters including the sampling rate of selected logging data, the sampling interval of longitudinal time and depth domain of the seismic data, Gardner formula coefficients, high and low frequency cutoff frequency, hard constraint trend, signal-to-noise ratio numerical values and the like according to the signal-to-noise ratio of seismic data and preprocessed logging data, and finally determining various parameter values by repeatedly adjusting the parameter values and comparing inversion test results to further generate a post-stack wave impedance body; extracting impedance at a well point and performing residual comparison calculation on the impedance at the well point and the impedance on the well according to the post-stack wave impedance body to obtain a wave impedance residual body;

according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; the iterative modification of the low-frequency model specifically includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of the seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: calculating original well point wave impedance according to the preprocessed well logging data, calculating a difference value between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error, judging whether the well point error of the corrected post-stack wave impedance body meets a set requirement, if so, taking the corrected post-stack wave impedance body as a post-stack wave impedance inversion impedance body, if not, taking the corrected low-frequency model as a low-frequency model, and repeating the steps 401 and 403.

And 5: determining relevant parameters of post-stack geostatistical inversion according to geological knowledge, post-stack wave impedance inversion impedance bodies and preprocessed logging data, wherein the relevant parameters comprise an xyz three-way variable range value, a base station value, a lump metal effect value, a sand-shale ratio and a geologic body strike angle of a variation function, and also comprise a probability distribution density function, a selection of a variation function fitting algorithm and the like.

Step 6: and taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to post-stack geostatistical inversion related parameters to obtain a post-stack inverted wave impedance residual error body.

And 7: and adding the post-stack inverted wave impedance residual error body and the post-stack wave impedance inverted impedance body for error correction to obtain a final post-stack wave impedance inverted impedance body for inversion of the fracture-cave reservoir stratum.

FIG. 2 illustrates a cross-sectional view of a final post-stack wave impedance inversion impedance volume according to one embodiment of the invention. The section diagram shows that the distribution range of underground fracture-cave reservoirs and the profiles of the reservoirs are quite clear, the shapes of fracture-cave reservoir spaces can be accurately defined, A, B drilling is finished when the drilling is met with target layer fractures, and the actual production result is as follows: the daily oil production of the well A is 27.68 ten thousand tons/day, no water exists, the distance between the well A and the weathering crust is about 30 meters, the daily oil production of the well B is 10.45 ten thousand tons/day, no water exists, the distance between the well A and the weathering crust is about 70 meters, the oil and gas production effect of the 2 wells is better, no water exists, the daily oil production and the stable production time are better, and the well C is a dry well. From the plan view, the development condition of the fracture-cavity reservoir body in the research area can be accurately outlined, the whole trend of the reservoir and the distribution range of the dominant reservoir are consistent with geological knowledge, and the actual drilling effect proves the accuracy of the carving of the fracture-cavity body of the plan view.

In conclusion, the wave impedance inversion result is obtained through an error iteration method, the wave impedance body is subjected to back correction according to the high-precision wave impedance residual body to obtain the high-precision inversion result, the goodness of fit between the fracture-cave reservoir body favorable reservoir stratum distribution plane diagram and the actual drilling production condition is higher, and the seismic inversion precision of the fracture-cave reservoir stratum is improved.

It will be appreciated by persons skilled in the art that the above description of embodiments of the invention is intended only to illustrate the benefits of embodiments of the invention and is not intended to limit embodiments of the invention to any examples given.

According to an embodiment of the invention, there is provided a fracture-cave reservoir inversion system, which is characterized by comprising: a memory storing computer-executable instructions; a processor executing computer executable instructions in the memory to perform the steps of: step 1: preprocessing the logging data of the area to be predicted to obtain preprocessed logging data; step 2: extracting well-passing seismic channels according to the post-stack seismic data, and performing seismic geological comprehensive calibration with the pre-processed logging data to obtain well side channel seismic wavelets; and step 3: establishing a low-frequency model according to the preprocessed logging data, the post-stack seismic data and the well side channel seismic wavelets; and 4, step 4: according to the wave impedance residual error body, carrying out iterative correction on the low-frequency model so as to obtain a post-stack wave impedance inversion impedance body; and 5: according to geological knowledge, a post-stack wave impedance inversion impedance body and the preprocessed logging data, determining post-stack geostatistical inversion related parameters; step 6: taking the iterated wave impedance residual error body as seismic input, and carrying out post-stack geostatistical inversion according to post-stack geostatistical inversion related parameters to obtain a post-stack inverted wave impedance residual error body; and 7: and carrying out error correction on the post-stack wave impedance inversion impedance body according to the post-stack inversion wave impedance residual error body to obtain a final post-stack wave impedance inversion impedance body.

In one example, step 4 further comprises: carrying out constraint development deterministic inversion on the well side channel seismic wavelets and the low-frequency model, adjusting and determining inversion parameters according to the signal-to-noise ratio of seismic data and the preprocessed logging data, and generating a post-stack wave impedance body; and extracting impedance at the well point and performing residual comparison calculation on the impedance on the well according to the post-stack wave impedance body to obtain a wave impedance residual body.

In one example, the iteratively modifying for the low frequency model of step 4 includes: step 401: correcting the low-frequency model by taking the wave impedance residual error body as a constraint condition of the seismic data item to obtain a corrected low-frequency model; step 402: obtaining a corrected post-stack wave impedance body according to the corrected low-frequency model; step 403: and judging whether the well point error of the corrected post-stack wave impedance body meets the set requirement, if so, taking the corrected post-stack wave impedance body as a post-stack wave impedance inversion impedance body, and if not, taking the corrected low-frequency model as a low-frequency model, and repeating the steps 401 and 403.

In one example, step 403 further comprises: calculating the wave impedance of an original well point according to the preprocessed logging data; and calculating the difference between the well point wave impedance extracted by the corrected post-stack wave impedance body and the original well point wave impedance to obtain a well point error.

In one example, the preprocessing of step 1 includes: borehole collapse correction, multi-well standardization and consistency processing.

According to the system, a wave impedance inversion result is obtained through an error iteration method, the wave impedance body is subjected to back correction according to the high-precision wave impedance residual error body to obtain a high-precision inversion result, the goodness of fit between the fracture-cave reservoir favorable reservoir distribution plane diagram and the actual drilling production condition is higher, and the precision of fracture-cave reservoir seismic inversion is improved.

It will be appreciated by persons skilled in the art that the above description of embodiments of the invention is intended only to illustrate the benefits of embodiments of the invention and is not intended to limit embodiments of the invention to any examples given.

Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.