阅读说明：本技术 裂缝网络复杂度评价方法及系统 (Crack network complexity evaluation method and system ) 是由 金其虎 于 2019-03-04 设计创作，主要内容包括：本发明提供了一种裂缝网络复杂度评价方法及系统,所述方法包含：通过微地震监测方法采集裂压时岩石破裂产生的弹性波动数据；分别对所述弹性波动数据中多个弹性波动定位,获得多个微地震事件；以所述微地震事件中任一微地震事件为中心,将多个预定数量的或相互关联的微地震事件组合获得微地震事件集合；根据所述微地震事件集合的各微地震事件的几何信息和运动信息计算获得所述微地震事件集合的几何形态复杂度、运动能量复杂度和统计密度复杂度；根据所述几何形态复杂度、所述运动能量复杂度和所述统计密度复杂度计算获得裂缝网络复杂度。(The invention provides a fracture network complexity evaluation method and a system, wherein the method comprises the following steps: elastic fluctuation data generated by rock fracture during fracturing is collected through a microseism monitoring method; respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events; combining a plurality of micro-seismic events with a predetermined number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set; calculating according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set to obtain the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set; and calculating according to the geometrical form complexity, the motion energy complexity and the statistical density complexity to obtain the fracture network complexity.)

1. A fracture network complexity evaluation method, the method comprising:

elastic fluctuation data generated by rock fracture during fracturing is collected through a microseism monitoring method;

respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events;

combining a plurality of micro-seismic events with a predetermined number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set;

calculating according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set to obtain the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set;

and calculating according to the geometrical form complexity, the motion energy complexity and the statistical density complexity to obtain the fracture network complexity.

2. The fracture network complexity evaluation method of claim 1, wherein the geometric information comprises at least spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

3. The fracture network complexity evaluation method of claim 2, wherein the obtaining of the geometric complexity of the micro-seismic event set by calculating the geometric information and the motion information of each micro-seismic event of the micro-seismic event set comprises: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number.

4. The fracture network complexity evaluation method of claim 2, wherein the calculating the motion energy complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set comprises: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number.

5. The fracture network complexity evaluation method of claim 2, wherein the calculating the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set comprises: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number.

6. The fracture network complexity evaluation method of claim 2, wherein calculating the fracture network complexity from the geometry complexity, the motion energy complexity, and the statistical density complexity comprises: and performing weighted average calculation on the geometric form complexity, the motion energy complexity and the statistical density complexity according to preset coefficients to obtain the fracture network complexity.

7. The fracture network complexity evaluation method of any of claims 3-6, wherein the predetermined size comprises a length of the set of microseismic events in one-dimensional space, an area of a two-dimensional space, a volume of a three-dimensional space, or a spatio-temporal of a four-dimensional space.

8. The fracture network complexity evaluation system is characterized by comprising a data acquisition module, an event set establishment module, a calculation module and an evaluation module;

the data acquisition module is used for acquiring elastic fluctuation data generated by rock fracture during fracturing by a microseism monitoring method; respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events;

the event set establishing module is used for combining a plurality of micro-seismic events with a preset number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set;

the calculation module is used for calculating and obtaining the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set;

and the evaluation module is used for calculating and obtaining the fracture network complexity according to the geometric form complexity, the motion energy complexity and the statistical density complexity.

9. The fracture network complexity evaluation system of claim 8, wherein the geometric information includes at least spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

10. The fracture network complexity evaluation system of claim 9, wherein the computation module further comprises a geometric complexity computation unit for dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number.

11. The fracture network complexity evaluation system of claim 9, wherein the computation module further comprises a motion energy complexity computation unit configured to divide the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number.

12. The fracture network complexity evaluation system of claim 9, wherein the computation module further comprises a statistical density complexity computation unit for dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number.

13. The fracture network complexity evaluation system of claim 9, wherein the evaluation module comprises a weighting unit, and the weighting unit is configured to perform weighted average calculation on the geometry complexity, the motion energy complexity, and the statistical density complexity according to preset coefficients to obtain the fracture network complexity.

14. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.

15. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.

Technical Field

The invention belongs to the field of geophysical exploration in wells, relates to a fracturing monitoring technology for yield increase transformation in oil and gas development, and particularly relates to a method and a system for evaluating the complexity of a fracture network based on statistical analysis.

Background

Hydraulic fracturing is an effective measure for increasing production and improving the yield of compact oil and gas. The fracturing fluid with higher viscosity is squeezed into a reservoir through a shaft by using a ground high-pressure pump. When the rate of injection of the fracturing fluid exceeds the absorptive capacity of the reservoir, a high pressure builds up in the reservoir at the bottom of the well, and when this pressure exceeds the fracture pressure of the rock near the bottom of the well, the reservoir will be forced open and create fractures. At this time, the fracturing fluid is continuously squeezed into the reservoir, and the fracture is continuously expanded into the reservoir. In order to keep the pressed-open fracture in an open state, then a sand carrying fluid with a propping agent (quartz sand, ceramsite and the like) is squeezed into the reservoir, and after the sand carrying fluid enters the fracture, the fracture can continue to extend forwards on the one hand, and the pressed-open fracture can be supported on the other hand, so that the pressed-open fracture is not closed any more. And then injecting a displacing fluid, completely displacing the sand-carrying fluid in the shaft into the fracture, and propping the fracture by using a propping agent. Finally, the injected fracturing fluid will automatically degrade and drain out of the wellbore, and the proppant will settle in these voids, leaving one or more fractures in the reservoir that create fluid communication between the reservoir and the wellbore.

In order to increase the complexity of the fracture network and improve the oil and gas productivity, students have conducted intensive research on the influence factors, the fracturing process and the like for forming the fracture network. Document 1 (stretch-pass optical and other scientific technology and engineering 2015.15(5)) adopts large-size true triaxial hydraulic fracturing simulation, and researches the influence of factors such as horizontal ground stress difference, pump injection displacement and shaft quantity on the fracture expansion rule of the compact shale gas reservoir; document 2 (zhanshi et al. petroleum institute. 2014.35(3)) develops a hydraulic fracturing fracture propagation simulation test on shale outcrops, and researches the influence of various factors on the fracturing fracture propagation rule of a compact shale horizontal well by observing the internal fracture morphology of a rock core after pressure measurement by using high-energy CT scanning; document 3 (the Weng dynasty is equal, natural gas geoscience, 2014.25(7)) establishes a mathematical model of a compact sandstone reservoir fracture network on the basis of physical simulation experiment results, researches a stress field by adopting a numerical simulation method, and tests various construction processes; the research on the temporary plugging diversion fracturing process is carried out in a document 4 (university of oil workers in the dynasty, the university of Jianghan. 2016.29(6)), and gas production profile data prove that the temporary plugging fracturing process is an effective way for improving the complexity of the artificial fracture network of the compact shale reservoir; document 5 (guo tiankui et al. geomechanical. 2013.34(4)) discusses a new evaluation method for fracture network formation ability by fracturing. The article tests the mechanical parameters of the rock for 10 rock cores, and contrasts and analyzes the precision of 3 common rock brittleness evaluation methods.

The microseism monitoring technology is a new geophysical technology which is started in 20 years, is an effective monitoring means for hydraulic fracturing, and can monitor the spatial form of a fracture network generated during fracturing in real time. When the formation breaks to create cracks, the elastic fluctuations are released. An observation system is arranged near the reservoir to collect elastic fluctuation signals, and a geophysical method is adopted, so that the stratum fracture position can be effectively positioned, and the reservoir characteristics after fracturing are further analyzed.

In summary, the current research on fracturing fracture networks focuses mainly on the aspect of fracturing process, i.e. how to optimize the fracturing process to increase the complexity of the fracture network. The detection method for the fracture network complexity mainly depends on the oil-gas yield difference after fracturing to make qualitative judgment. No published literature or report on the application of microseismic techniques to evaluate the complexity of a fracture network has been found, nor has detailed descriptions and specific details of evaluating the complexity of a fracture network based on microseismic techniques been published.

Disclosure of Invention

The invention aims to provide a method and a system for evaluating the complexity of a fracture network based on statistical analysis, aiming at solving the problem of evaluating the complexity of the fracture network formed by the conventional reservoir fracturing modification. The method quantitatively describes the complexity of the network distribution of fractured reservoirs from the angles of geometric forms, motion energy and statistical density, and is used for quantitative fracturing process research, oil reservoir modeling digital-analog research and the like.

Specifically, the fracture network complexity evaluation method includes: elastic fluctuation data generated by rock fracture during fracturing is collected through a microseism monitoring method; respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events; combining a plurality of micro-seismic events with a predetermined number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set; calculating according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set to obtain the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set; and calculating according to the geometrical form complexity, the motion energy complexity and the statistical density complexity to obtain the fracture network complexity.

In an embodiment of the present invention, the geometric information at least includes spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

In an embodiment of the present invention, the obtaining the complexity of the geometric shape of the micro-seismic event set by calculating the geometric information and the motion information of each micro-seismic event of the micro-seismic event set includes: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number.

In an embodiment of the present invention, the obtaining of the motion energy complexity of the micro-seismic event set by calculating the geometric information and the motion information of each micro-seismic event of the micro-seismic event set includes: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number.

In an embodiment of the present invention, the calculating and obtaining the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set includes: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number.

In an embodiment of the present invention, the calculating and obtaining the fracture network complexity according to the geometry complexity, the motion energy complexity, and the statistical density complexity includes: and performing weighted average calculation on the geometric form complexity, the motion energy complexity and the statistical density complexity according to preset coefficients to obtain the fracture network complexity.

In one embodiment of the invention, the predetermined size comprises the length of the set of microseismic events in a one-dimensional space, the area of a two-dimensional space, the volume of a three-dimensional space, or the spatio-temporal of a four-dimensional space.

The invention also provides a fracture network complexity evaluation system, which comprises a data acquisition module, an event set establishment module, a calculation module and an evaluation module; the data acquisition module is used for acquiring elastic fluctuation data generated by rock fracture during fracturing by a microseism monitoring method; respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events; the event set establishing module is used for combining a plurality of micro-seismic events with a preset number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set; the calculation module is used for calculating and obtaining the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set; and the evaluation module is used for calculating and obtaining the fracture network complexity according to the geometric form complexity, the motion energy complexity and the statistical density complexity.

In an embodiment of the present invention, the geometric information at least includes spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

In an embodiment of the invention, the computation module further comprises a geometric complexity computation unit, the geometric complexity computation unit is used for dividing the micro-seismic event set with a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number.

In an embodiment of the invention, the computation module further comprises a motion energy complexity computation unit, wherein the motion energy complexity computation unit is used for dividing the micro-seismic event set with a preset size into a preset number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number.

In an embodiment of the present invention, the calculation module further includes a statistical density complexity calculation unit, where the statistical density complexity calculation unit is configured to divide the micro-seismic event set with a predetermined size into a predetermined number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number.

In an embodiment of the present invention, the evaluation module includes a weighting unit, and the weighting unit is configured to perform weighted average calculation on the geometric form complexity, the motion energy complexity, and the statistical density complexity according to a preset coefficient to obtain the fracture network complexity.

The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.

The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.

The invention has the beneficial technical effects that: from the three aspects of geometric attributes, motion attributes and statistical attributes, the complexity of the fracture network distribution formed after reservoir fracturing is described quantitatively, and the fracturing effect is effectively quantified; the parameter can also be used for quantitative fracturing process research, fracturing parameter optimization research and oil reservoir modeling digital-analog research, and has great significance for oil reservoir development.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:

fig. 1 is a schematic flow chart of a fracture network complexity evaluation method according to an embodiment of the present invention;

FIG. 2 is a diagram illustrating a manner in which event subsets are partitioned according to an embodiment of the present invention;

fig. 3 is a schematic flowchart of a fracture network complexity evaluation method according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a fracture network complexity evaluation system according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a fracture network complexity evaluation system according to an 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 present invention is described in further detail below with reference to the embodiments and 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.

Referring to fig. 1, the method for evaluating the complexity of a fracture network provided by the present invention includes: s101, acquiring elastic fluctuation data generated by rock fracture during fracturing by a microseism monitoring method; s102, positioning a plurality of elastic fluctuations in the elastic fluctuation data respectively to obtain a plurality of microseism events; s103, combining a plurality of micro-seismic events with a preset number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set; s104, calculating according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set to obtain the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set; and S105, calculating according to the geometric form complexity, the motion energy complexity and the statistical density complexity to obtain the fracture network complexity. Wherein the geometric information comprises at least spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

Referring to fig. 2, in the above embodiment, the step S104 of obtaining the geometric complexity, the motion energy complexity, and the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set includes: dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number. Dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number. Dividing the set of microseismic events of a predetermined size into a predetermined number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number. Wherein the predetermined size comprises a length of the collection of microseismic events in a one-dimensional space, an area of a two-dimensional space, a volume of a three-dimensional space, or a spatio-temporal of a four-dimensional space.

In the above embodiment, the step S105 of calculating and obtaining the fracture network complexity according to the geometry complexity, the motion energy complexity, and the statistical density complexity includes: and performing weighted average calculation on the geometric form complexity, the motion energy complexity and the statistical density complexity according to preset coefficients to obtain the fracture network complexity.

For a more clear description of the fracture network complexity evaluation method provided by the present invention, the following embodiments are taken as a whole to illustrate, and it should be understood by those skilled in the art that the following description is only for assisting understanding of the fracture network complexity evaluation method provided by the present invention, and is not limited thereto.

Referring to fig. 3, overall, a specific flow of the fracture network complexity evaluation method provided by the present invention is as follows:

s301, acquiring elastic fluctuation generated when rocks break during fracturing by adopting a microseism monitoring technology, wherein each elastic fluctuation is called a microseism signal, positioning the microseism signals, and acquiring microseism events, wherein each microseism event comprises geometrical information and motion information of rock break; wherein the geometric information should at least include spatial coordinates; the motion information at least comprises amplitude, energy, magnitude and frequency; the motion information refers to one or more attributes of event amplitude, energy, magnitude and frequency;

s302, combining a plurality of adjacent or mutually related micro-seismic events by taking a certain event as a center to form a micro-seismic event set;

s303, calculating the complexity of the geometric shape, the complexity of the motion energy and the complexity of the statistical density of the event set based on the event set;

the geometric complexity Cg of the event set is calculated by dividing the event set SE with a size V into n subsets SEi (i is 1,2 … n), wherein the number m of subsets that are not empty is a percentage of all the subsets, and is defined as the geometric complexity of the event set, and the geometric complexity ranges from 0 to 1, and the larger the value is, the more complicated the representation is. The above process can be described using the following mathematical formula, but not the only mathematical description:

C_GV(n)＝(100*m/n)％

the motion energy complexity Ck of the event set is calculated by dividing the event set SE with the size V into n subsets SEi (i is 1,2 … n), wherein the sum of certain motion information of the ith subset is ARi, and AR1> -AR 2> -AR 3> - … > -ARn. The sum of the motion information is greater than or equal to the first p subsets of the E%, the sum of the motion information accounts for the percentage of the total number of the subsets, the motion energy complexity of the event set energy information is defined to be not less than the E%, the numerical range of the motion energy complexity is 0 to 1, and the larger the value is, the more complex the representation is. The above process can be described using the following mathematical formula, but not the only mathematical description:

where c1 is a motion information correction coefficient.

Calculating the statistical density complexity Cs of the event set means that the event set SE with the size V is divided into n subsets SEi (i ═ 1,2 … n), the statistical information of the ith subset is summed up to MBi, and MB1> -MB 2> -MB 3> -MB … > -MBn. The first p subsets with the information sum being more than or equal to D percent account for the total number of the subsets and are defined as the statistical density complexity of the event set density information being not less than D percent, the numerical range of the statistical density complexity is 0 to 1, and the larger the value is, the more complicated the representation is. The above process can be described using the following mathematical formula, but not the only mathematical description:

where c2 is the statistical information correction coefficient.

It should be noted that the event set size V refers to the length of a one-dimensional space, or the area of a two-dimensional space, or the volume of a three-dimensional space, or the space-time of a four-dimensional space;

s304, evaluating the complexity of a fracture network according to the complexity of the geometric form, the complexity of motion energy and the complexity of statistical density; the calculation of the fracture network complexity refers to firstly dividing the fracture network complexity Cf into q levels, respectively representing the q levels by (Cf1, Cf2 … Cfq), respectively projecting the geometric form complexity, the motion energy complexity and the statistical density complexity to the fracture network complexity Cf, and respectively representing the projected geometric form complexity, the motion energy complexity and the statistical density complexity as gCf, kCf and sCf. The fracture network complexity is defined as gCf, kCf and sCf weighted average, and the weighting is used for representing the contribution size of geometric attributes, motion attributes and statistical attributes to the fracture network complexity.

According to the projection mode, the Cg, Ck and Cs can be divided into q parts from 0 to 1, and if Cg, Ck or Cs falls into the ith part, gCf or kCf or cCf is set as Cfi correspondingly. The following mathematical form may be used, but is not the only mathematical description:

gCf＝αCg，kCf＝βCk，sCf＝γCs

wherein x is_i,y_i,z_iIs a real number from 0 to 1, but does not contain 0 and 1, and the value can be calculated by the following formula:

in the above embodiment, since there may be a problem of different kinematic attributes when calculating the motion energy complexity, in actual work, the process of calculating the motion energy complexity may be further performed as follows:

according to the motion energy complexity Ck, an event set SE with a size V is divided into n subsets SEi (i is 1,2 … n), and the sum of the kinematic attributes of the ith subset is AR_ji, and AR_j1>＝AR_j2>＝AR_j3>＝…>＝AR_jn, table j below represents different kinematic properties. The sum of the motion information is greater than or equal to the first p subsets of the E%, the sum of the motion information accounts for the percentage of the total number of the subsets, the motion energy complexity of the event set energy information is defined to be not less than the E%, the numerical range of the motion energy complexity is 0 to 1, and the larger the value is, the more complex the representation is. The above process can be described using the following mathematical formula, but not the only mathematical description:

where cj is the respective motion information correction coefficient.

Referring to fig. 4, the present invention further provides a fracture network complexity evaluation system, which includes a data acquisition module, an event set establishment module, a calculation module, and an evaluation module; the data acquisition module is used for acquiring elastic fluctuation data generated by rock fracture during fracturing by a microseism monitoring method; respectively positioning a plurality of elastic fluctuations in the elastic fluctuation data to obtain a plurality of microseism events; the event set establishing module is used for combining a plurality of micro-seismic events with a preset number or mutual correlation by taking any one of the micro-seismic events as a center to obtain a micro-seismic event set; the calculation module is used for calculating and obtaining the geometric form complexity, the motion energy complexity and the statistical density complexity of the micro-seismic event set according to the geometric information and the motion information of each micro-seismic event of the micro-seismic event set; and the evaluation module is used for calculating and obtaining the fracture network complexity according to the geometric form complexity, the motion energy complexity and the statistical density complexity. Wherein the geometric information comprises at least spatial coordinates; the motion information at least comprises one of amplitude, energy, magnitude and frequency; the statistical information of the micro-seismic event set comprises the number of events.

In the above embodiment, the evaluation module includes a weighting unit, and the weighting unit is configured to perform weighted average calculation on the geometric form complexity, the motion energy complexity, and the statistical density complexity according to a preset coefficient to obtain the fracture network complexity.

Referring to fig. 5, in an embodiment of the present invention, the computation module further includes a geometric complexity computation unit, a motion energy complexity computation unit, and a statistical density complexity computation unit, where the geometric complexity computation unit is configured to divide the micro-seismic event set with a predetermined size into a predetermined number of subsets; and obtaining the geometric form complexity according to the number of the subsets which are not empty and the percentage value of the predetermined number. The motion energy complexity calculating unit is used for dividing the micro-seismic event set with a preset size into a preset number of subsets; and obtaining the motion energy complexity according to the percentage value of the subset with the motion information sum larger than or equal to the preset motion energy complexity and the preset number. The statistical density complexity calculation unit is used for dividing the micro-seismic event set with a preset size into a preset number of subsets; and obtaining the statistical density complexity according to the percentage value of the subset with the statistical information sum larger than or equal to the preset statistical density complexity and the preset number.

The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.

The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.

The invention has the beneficial technical effects that: from the three aspects of geometric attributes, motion attributes and statistical attributes, the complexity of the fracture network distribution formed after reservoir fracturing is described quantitatively, and the fracturing effect is effectively quantified; the parameter can also be used for quantitative fracturing process research, fracturing parameter optimization research and oil reservoir modeling digital-analog research, and has great significance for oil reservoir development.

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.