Microseismic event point separation method based on logging constraint

Abstract

The invention relates to a microseism event point separation method and system based on logging constraint, and the method comprises the steps: analyzing curve energy differentiation characteristics through logging data, and calculating a crack strength curve; extracting the energy level, depth and spatial position of the microseism event, and determining the three-dimensional distribution characteristics of the microseism event; constructing a fracture network form based on the time sequence and the spatial position of the microseism event; then, interactive analysis is carried out on the microseismic event B value and the logging crack strength, and energy compensation is carried out on the microseismic energy level; primary and secondary cracks are distinguished according to the energy conservation principle of fracturing fluid; and evaluating a power law relationship between the number of the microseism events and the magnitude to form systematic statistical analysis. According to the method, by combining logging information and a microseism monitoring technology, the problem of energy attenuation in a traditional method is effectively solved, the reliability and precision of microseism event separation are improved, a scientific basis is provided for fracturing construction, and efficient development of oil and gas resources is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and in particular to a method for hydraulic fracturing microseismic positioning processing, natural fracture microseismic event point identification and separation. Background Art

[0002] As a clean energy, the development and utilization of shale gas will help reduce China's dependence on external energy and improve energy security. The domestic deep shale gas resources have great potential, and the development process involves a series of complex engineering and technical issues, such as horizontal drilling and hydraulic fracturing. Affected by the casing change and fracturing channeling, the development effect is not as expected, which restricts the scale-effective development process; the challenge of accurate imaging of deep shale reservoirs has increased, natural fractures are multi-scale, and the prediction accuracy and resolution are difficult to fully meet production needs; at the same time, the existing natural fracture prediction methods are insufficient, and there is a lack of systematic reliability evaluation methods for the prediction results. Luzhou deep shale gas adopts the development method of "horizontal well drilling + volume fracturing". At present, the deep shale gas in Luzhou area is mainly affected by casing change and hydraulic fracturing channeling, which leads to great difficulties in development. The development effect in Luzhou area is not as expected. The development characteristics of natural fractures are important indicators for adjusting fracturing construction parameters, which are very important for the optimization of development plans. If the natural fractures are not correctly identified and handled during the fracturing process, it may lead to risks such as deformation of the production well casing or fracturing channeling. Accurate characterization and identification of natural fractures in the reservoir and taking corresponding measures to adjust fracturing parameters and construction plans can reduce development risks, improve fracturing effects, and guide the design of subsequent fracturing plans to better optimize resource utilization and improve development benefits.

[0003] In view of the above resource demands and development characteristics, there is an urgent need for a method that can accurately predict natural fractures and accurately characterize natural fractures. Currently, conventional natural fracture identification technologies mainly include two types: seismic attribute prediction method and hydraulic fracturing microseismic monitoring method.

[0004] Seismic attribute prediction method: Seismic attributes (curvature, coherence) reflect from different angles the deformation and rupture of the stratum when it is squeezed by tectonic stress. By calculating the curvature and coherence attributes, the development of fractures in the stratum can be predicted. The prediction range is large, but the prediction accuracy is relatively low.

[0005] Hydraulic fracturing microseismic monitoring method: collect microseismic waveform signals generated during the fracturing process, process and locate the screened microseismic events generated during the fracturing process, and describe the crack morphology and spatial distribution law generated by fracturing. This method is mainly based on the energy generated by the microseismic event points. The B-value analysis method is used to separate artificial fractures and natural fractures, that is, to determine the threshold values ​​of different fracture event points, so as to separate the microseismic event points. However, the calculation uses a single data and cannot be verified, and does not take into account the energy absorption and loss of the cracks during the propagation of seismic waves, thereby reducing the accuracy of event point separation.

[0006] This patent adopts multidisciplinary technical ideas and means, proposes the basic principles and calculation methods of the method, and shows through theoretical calculations and error analysis that the method is reasonable and effective. At the same time, it uses multi-information fusion to interpret the natural fracture characteristics of logging data, and then separates the microseismic event points after energy compensation. This method makes up for the technical problem that traditional separation methods do not consider energy loss and thus affect the separation accuracy. This method has the technical advantages of strong practicality and high prediction accuracy. Summary of the invention

[0007] In view of the defects of the prior art, the present invention provides a method for separating microseismic event points based on logging constraints. Based on the microseismic data collected in real time during the hydraulic fracturing construction process, the effective information is extracted and analyzed, and the microseismic events that are located or relocated in real time are grouped according to space, time and energy level. The energy differentiation characteristics of the logging data analysis curve are combined to clarify the spatial position of the fracture development well section. On this basis, the B value of the microseismic event and the logging fracture intensity curve are interactively analyzed, and the specific microseismic separation plan is finally determined. The advantages of the wide range of fracture prediction of microseismic data attributes and the high accuracy of logging data are fully utilized, and the reliability and accuracy of microseismic data separation and natural fracture identification are improved, thereby improving the prediction accuracy of natural fractures in the reservoir, which is conducive to guiding fracturing construction and improving fracturing effects.

[0008] In order to achieve the above invention object, the technical solution adopted by the present invention is as follows:

[0009] A microseismic event point separation method based on well logging constraints comprises the following steps:

[0010] (a) Using well logging data, we analyze the energy differentiation characteristics of the well logging data curve and calculate the fracture strength curve as a condition constraint for subsequent microseismic data separation;

[0011] (b) Extract the energy level, depth and spatial location information of microseismic event data and clarify the distribution law and characteristics of microseismic event points in three-dimensional space;

[0012] (c) Based on the timing and spatial location of microseismic events, the fracture network morphology is constructed, assuming that new fractures are likely to extend from existing fractures;

[0013] (d) Interactive analysis of the B value of microseismic events and the logging fracture intensity curve is performed, and energy compensation of microseismic energy levels is performed based on the fracture development intensity at different depths;

[0014] (e) Based on the energy conservation principle of fracturing fluid, primary and secondary fractures are distinguished, and the relationship between the number of fracture branches and the width, conductivity and pressure transmission of the main fracture is analyzed;

[0015] (f) Evaluate the power law relationship between the number of microseismic events and their magnitude, calculate the B values ​​of different well sections, and form a systematic statistical analysis;

[0016] (g) Based on the energy-compensated microseismic information data, the separation scheme of microseismic event points is finally determined to achieve effective classification of natural fractures and reservoir matrix.

[0017] Furthermore, the calculation of the fracture strength curve is based on the anisotropic characteristics of the logging data and the fracture porosity analysis to provide a more accurate fracture strength assessment.

[0018] Furthermore, the energy compensation is achieved by correcting the microseismic energy level to accurately reflect the effect of crack strength on microseismic energy.

[0019] Furthermore, the power law relationship is obtained by statistically analyzing the frequency and magnitude distribution of microseismic events to form a linear model to support the prediction of microseismic events.

[0020] Furthermore, the separation scheme has been verified multiple times using different test data to ensure the accuracy and reliability of the results.

[0021] The present invention also discloses a microseismic event point separation system, which can be used to implement the above-mentioned microseismic event point separation method, specifically comprising:

[0022] Data acquisition module: responsible for collecting logging data and microseismic event data, including energy level, depth and spatial location information.

[0023] Data preprocessing module: noise filtering, standardization and format conversion of the collected logging data and microseismic event data for subsequent analysis.

[0024] Energy analysis module: Analyze the energy differentiation characteristics of logging data curves, calculate fracture strength curves, and provide conditional constraints for microseismic data separation.

[0025] Spatial distribution analysis module: extract the spatial distribution law of microseismic events and construct the network morphology of microseismic events in three-dimensional space.

[0026] Interactive analysis module: Interactive analysis of the B value of microseismic events and the logging fracture intensity curve, combined with the fracture development intensity at different depths, to perform energy compensation for the microseismic energy level.

[0027] Primary and secondary fracture analysis module: Based on the energy conservation principle of fracturing fluid, primary and secondary fractures are distinguished, and the relationship between the number of fracture branches and the width, conductivity and pressure transmission of the main fracture is analyzed.

[0028] Statistical analysis module: evaluates the power law relationship between the number of microseismic events and the magnitude, counts the B values ​​of different well sections, and forms a systematic statistical analysis.

[0029] Event point separation module: Based on the energy-compensated microseismic information data, the separation scheme of microseismic event points is finally determined to achieve effective classification of natural fractures and reservoir matrix.

[0030] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned microseismic event point separation method when executing the program.

[0031] The present invention also discloses a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned microseismic event point separation method is implemented.

[0032] Compared with the prior art, the advantages of the present invention are:

[0033] The present invention gives full play to the wide range of fracture prediction capabilities of microseismic data and the high precision advantages of well logging data, organically combines microseismic monitoring technology with high-precision well logging interpretation schemes, and solves the problem that traditional methods do not consider the energy attenuation of seismic waves during propagation in different media. By combining well logging data with quantitative interpretation of natural fractures and energy compensation of microseismic event points, the recognition of artificial fractures and natural fractures is significantly improved. The energy level intensity and data correlation after compensation are improved, realizing the complementary advantages of data from different disciplines, and reasonably and objectively improving the separation of microseismic events and the reliability and accuracy of identifying natural fractures. In addition, the accuracy of the model is verified by actual fracturing data, which further ensures the accuracy of the model and helps to guide fracturing construction and improve fracturing effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of a method for separating microseismic event points according to an embodiment of the present invention;

[0035] Figure 2 This is a result diagram of the interpretation of the fracture strength curve of the well logging data according to an embodiment of the present invention;

[0036] Figure 3 is a statistical histogram of effective information energy levels of microseismic event points according to an embodiment of the present invention;

[0037] Figure 4 This is a statistical analysis diagram of the B value of a microseismic event and the fracture strength interpreted by well logging according to an embodiment of the present invention;

[0038] Figure 5 is a diagram of real-time positioning or post-processing positioning results of microseismic events according to an embodiment of the present invention;

[0039] Figure 6 is a schematic diagram of microseismic energy compensation according to an embodiment of the present invention;

[0040] Figure 7 This is a B-value analysis diagram of a microseismic event in an embodiment of the present invention (without energy compensation);

[0041] Figure 8 This is a B-value analysis diagram of a microseismic event in an embodiment of the present invention (energy compensation has been performed);

[0042] Fig. 9 This is a comparison diagram of the microseismic energy supplementation and well logging identification results in the embodiment of the present invention;

[0043] Fig.10 This is a comparison diagram of the earthquake prediction results before and after the micro-seismic energy supplementation according to the embodiment of the present invention;

[0044] Fig.11 : is a microseismic event point separation result diagram (cracks) of an embodiment of the present invention;

[0045] Fig.12 is a microseismic event point separation result map (matrix) according to an embodiment of the present invention;

[0046] Fig.13 It is a verification diagram of engineering construction parameters of an embodiment of the present invention (H56 platform);

[0047] Fig.14 It is a verification diagram of engineering construction parameters of an embodiment of the present invention (H58 platform);

[0048] Fig.15 It is a comparison diagram of the matching rate before and after microseismic energy compensation according to an embodiment of the present invention (and the logging interpretation results). DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and examples.

[0050] like Figure 1 As shown, this embodiment mainly includes 6 steps; first, the energy differentiation characteristics of the logging data analysis curve are used to calculate the fracture intensity curve for the subsequent microseismic data separation condition constraint; then, the effective information such as the energy level, depth and spatial position of the microseismic event data is extracted to clarify the distribution law and characteristics of the microseismic event points in three-dimensional space, and according to the properties such as the timing and position of the microseismic event, the new fractures are likely to extend from the existing fractures to construct the fracture network morphology. On this basis, the B value of the microseismic event and the logging fracture intensity curve are interactively analyzed, and the energy compensation of the microseismic energy level is carried out in combination with the fracture development intensity at different depths. According to the conservation of fracturing fluid energy, the primary and secondary fractures are distinguished. The more fracture branches, the wider the main fracture, the stronger the conductivity and the stronger the pressure transmission; then, the natural fracture communication evaluation based on the B value of the microseismic event is carried out, and the number of microseismic events and their magnitudes have a power law relationship. Statistical analysis of microseismic data was performed to establish B values ​​for different well sections. Based on the microseismic information data after energy compensation, a microseismic event point separation scheme was finally determined to achieve the classification of natural fractures and reservoir matrix. The separation results were finally verified using fracturing production data.

[0051] The energy and velocity differences between fast and slow shear waves are usually expressed as percent anisotropy:

[0052]

[0053] Where: P e ——is the energy percentage anisotropy;

[0054] E q —— is the energy of fast transverse waves;

[0055] E sl ——is the energy of slow transverse waves.

[0056]

[0057] Where: Pt - the percentage anisotropy of the time difference;

[0058] dt ssl —— is the time difference of slow shear waves;

[0059] dt sq ──It is the time difference of rapid transverse waves.

[0060] The main factors leading to shear wave anisotropy include uneven horizontal stress, open cracks, faults, high-angle formation bedding, and the influence of elliptical boreholes. In the corresponding cases, the fast shear wave azimuth corresponds to the direction of the maximum horizontal principal stress or the direction of the fault / crack and the direction of the formation bedding. Combining the dual lateral resistivity fracture porosity, Stoneley wave attenuation fracture indication curve, fast and slow shear wave anisotropic fracture indication characteristics, combined with the fracture porosity interpreted by electrical imaging (FVPA), a comprehensive fracture indication curve (FVPA_PRED) was established using a neural network method.

[0061] Based on the effective signal of the microseismic event, the spatial position, time of occurrence and magnitude of the earthquake are located, and the generation and development process and characteristics of the fracturing cracks and fracture network are inverted to determine the length, width, height and direction of the fracture network formed by the reservoir transformation. After screening, noise suppression, spatial positioning and other processing, the waveform signal recorded by the detector will eventually be processed into a microseismic event point. The position of the microseismic event point represents the vibration position, and the size of the microseismic event point represents the magnitude of the vibration. The top view of the microseismic event is the result of the microseismic event point projected on the XY plane. The extension length of the microseismic event point in the vertical well trajectory direction on the top view is defined as the length of the artificial fracture network, the extension length of the microseismic event point along the well trajectory direction is defined as the width of the artificial fracture network, and the direction of the artificial fracture grid length is defined as the distribution direction of the microseismic event point. The side view of the microseismic event is the result of the microseismic event point projected on the Z plane, and its height on the Z plane is defined as the height of the artificial fracture network.

[0062] Normally, the microseismic energy level induced by hydraulic fracturing is low, ranging from -3 to -0.5. The energy of this microseismic wave attenuates significantly with the increase of observation distance. Some of the energy attenuation is caused by normal energy loss caused by the vibration of reservoir rocks during the propagation path, and some of the energy attenuation is caused by abnormal energy attenuation due to geological reasons, such as passing through natural fractures and different lithological interfaces. It should be noted that if the energy of the received microseismic signal is abnormal, it is necessary to analyze the energy attenuation of the seismic wave between the observation system and the signal seismic location. This paper analyzes the relationship between energy attenuation and natural fractures during the propagation of microseismic energy levels at different observation locations, and proposes an accurate evaluation method for compensation of seismic wave energy attenuation. This method avoids the prediction error caused by low signal recognition accuracy of microseismic events by compensating for the attenuation of seismic wave energy, realizes accurate processing of microseismic events, conducts analysis on fracture strength, artificial fracture complexity index and B value of different wells, statistically analyzes the relationship between fracture strength and artificial fracture complexity index and B value of different fracturing sections, and uses fracture strength interpreted by well logging to compensate for microseismic energy:

[0063] M=M0*e f

[0064] In the above formula, the microseismic energy level without energy compensation is M0, the crack strength is f, and M is the microseismic energy that has completed energy compensation.

[0065] Microseismic events can be described by the b-values ​​of their frequency-magnitude distribution. The Gutenberg-Richer relationship is as follows:

[0066] log N(m>M)=a-bM

[0067] In the above formula, N is the number of events with magnitude greater than M. The b value is the slope of the linear part of the log(N) vs. M plot. This plot has negative curvature for smaller values ​​of M due to the oversampling caused by the detection threshold. The resulting linear mutation is called the absolute minimum magnitude, M c .

[0068] On this basis, the microseismic event point separation scheme is determined to guide the prediction of natural fractures, and the actual fracturing construction curve is used to verify and analyze the prediction results.

[0069] like Figure 2 As shown in the figure, the main purpose of the orthogonal dipole measurement (BCR) measurement method is to measure the shear wave anisotropy of the formation. In fractured formations caused by tectonic stress or other geological factors, the shear wave velocity usually shows azimuthal anisotropy. The shear wave velocity of the particle vibrating parallel to the fracture direction and propagating along the well axis is faster than the shear wave velocity of the particle vibrating perpendicular to the fracture direction and propagating along the well axis. If the particle vibration direction caused by the shear wave is at an angle to the fracture direction, the incident shear wave splits into fast and slow shear waves in which the particles vibrate parallel and perpendicular to the fracture direction and propagate along the well axis at different speeds, i.e., the shear wave splitting phenomenon. It is worth pointing out that this shear wave splitting phenomenon exists not only in fractured formations, but also in non-fractured formations with unbalanced ground stress, i.e., in formations with strong anisotropy; when the formation dip angle is large and the bedding is developed, it will also show strong anisotropy. The indicators for measuring formation anisotropy include: fast and slow shear wave percentage energy difference, anisotropy indication based on time difference and anisotropy indication based on time. Based on the above theory, the single well fracture strength curve can be calculated, which is used to formulate natural fracture and reservoir matrix separation scheme in combination with microseismic B value.

[0070] like Figure 3 As shown in the figure, a statistical analysis of the energy levels of natural cracks caused by hydraulic fracturing was conducted, and a total of 5770 event points were analyzed. The energy level distribution range of the platform microseismic event points was: -2.434 to 1.635. The analysis results showed that the platform had a high proportion of large-magnitude events and was greatly affected by natural cracks.

[0071] like Figure 4As shown in the figure, the fracture strength, artificial fracture complexity index and B value of different wells were analyzed, and the relationship between the fracture strength of different fracturing sections of horizontal wells and the artificial fracture complexity index and B value was statistically analyzed. When the fracture strength was greater than 0.02, the fracture complexity index and the natural fracture B value increased significantly.

[0072] like Figure 5 As shown in the figure, using the microseismic monitoring data generated by actual fracturing construction, the spatial position of the event point and the time of earthquake occurrence can be clearly located, and the energy level corresponding to different event points can be characterized, providing a data basis for event point separation.

[0073] exist Figure 6 In the figure, microseismic waves propagate from the earthquake source to three detectors. After the earthquake source ruptures, the microseismic waves reach detectors G1, G2 and G3 according to their respective propagation times. The microseismic signals received at the detector end show different degrees of attenuation. However, there are no natural cracks on the way from the microseismic event point to the G1 detector. This is the normal attenuation of energy with the propagation distance. There are natural cracks between the earthquake source and G2 and G3. Our method is to reversely compensate the energy of the receiving signals of each detector along the propagation path to compensate for the extra energy loss caused by the existence of natural cracks.

[0074] like Figure 7 As shown in the figure, the B value analysis technology is used to calculate the B value of the microseismic event point. The horizontal axis is the energy level value, and the vertical axis is the number of microseismic data corresponding to the energy level, expressed in logarithms. A tangent is drawn at a relatively smooth position of the statistical curve, and its slope is the B value.

[0075] like Figure 8 As shown in the figure, energy compensation is performed on the collected microseismic time points in combination with the logging interpretation results. After compensation, the slope of the B value increases significantly, reflecting that the energy strength of different event points is significantly different. This shows that the energy compensation scheme can improve the recognition of artificial fractures and natural fractures. The absolute minimum magnitude increases from 0.82 to 1.04, the energy compensation increment is 26.8%, and the data correlation also increases from 0.9974 to 09985. Figure 8 As shown in the figure, combined with the single well fracture prediction curve, the seismic fracture prediction model is adjusted to obtain Figure 8 It can be seen that the fracture prediction accuracy is significantly increased after single well disturbance, and the matching rate is improved by more than 30%.

[0076] like Fig. 9 As shown in the figure, a comparison is made between the single well fracture prediction curve and the natural fracture strength predicted by microseismic. The comparison results show that the correlation coefficient is increased from 0.6419 to 0.8341 after energy compensation, which provides an accurate data basis for subsequent attribute disturbance.

[0077] like Fig.10 As shown in the figure, combined with the fracture prediction curve after energy compensation, the 3D seismic fracture prediction model is adjusted. Fig. 9 It can be seen that the fracture prediction accuracy is significantly increased after single well disturbance, and the matching rate is improved by more than 30%.

[0078] like Fig.11 As shown in the figure, a separation plan was developed in combination with the logging interpretation results to carry out the division of response characteristics of different types of microseismic event points on the platform, and the separation of microseismic events was completed. Events with magnitudes greater than the threshold are basically microseismic events caused by natural fractures, showing an irregular trend of extending along the direction of natural fractures. For large-scale faults, the microseismic response characteristics are as follows: the fracture energy level is relatively high, indicating a violent energy release, and the earthquake time and location are not fixed, and the extension distance is greater than 1000m.

[0079] like Fig.12 As shown in the figure, events with magnitudes less than the threshold are basically caused by the expansion of artificial fracture networks. The microseismic event points formed by the matrix reservoir are generally symmetrically distributed at both ends of the wellbore, with the smallest energy level event points and the shortest lateral distance of spatial extension, and the data distribution is relatively neat.

[0080] like Fig.13 As shown in the figure, due to the serious filtration loss of large-scale natural fractures, when the fracturing fluid enters the fracture zone, the pump pressure will be significantly reduced. The fracturing operation of the four wells in the Lu 203H56 platform at the location of large-scale development has obvious pressure drop characteristics. The pressure drop time is positively correlated with the distance between the spatial location of the fracture development and the wellbore. The relevant well section construction parameters are selected to verify it. The accuracy of the Lu 203H56 platform model is verified by engineering parameters.

[0081] like Fig.14 As shown in the figure, the fracturing construction data show that the five wells of the Lu 203H58 platform have obvious pressure drop characteristics at the locations where large-scale fractures are developed. Due to the serious filtration loss of large-scale natural fractures, when the fracturing fluid enters the fracture zone, the pump pressure will be significantly reduced. The accuracy of the Lu 203H58 platform model is verified by engineering parameters.

[0082] like Fig.15 As shown in the figure, based on the comparison of the agreement rate between the natural fracture interpretation before and after microseismic energy compensation and well logging, it can be seen that before energy compensation, the agreement rate between the natural fractures identified by microseismic and the well logging interpretation was only 70%, with green indicating agreement and red indicating disagreement; before energy compensation, the agreement rate increased to 83.3%, indicating that this technology can effectively improve the agreement rate.

[0083] In another embodiment of the present invention, a microseismic event point separation system is provided. The system can be used to implement the above-mentioned microseismic event point separation method, specifically including:

[0084] Data acquisition module: responsible for collecting logging data and microseismic event data, including energy level, depth and spatial location information.

[0085] Data preprocessing module: noise filtering, standardization and format conversion of the collected logging data and microseismic event data for subsequent analysis.

[0086] Energy analysis module: Analyze the energy differentiation characteristics of logging data curves, calculate fracture strength curves, and provide conditional constraints for microseismic data separation.

[0087] Spatial distribution analysis module: extract the spatial distribution law of microseismic events and construct the network morphology of microseismic events in three-dimensional space.

[0088] Interactive analysis module: Interactive analysis of the B value of microseismic events and the logging fracture intensity curve, combined with the fracture development intensity at different depths, to perform energy compensation for the microseismic energy level.

[0089] Primary and secondary fracture analysis module: Based on the energy conservation principle of fracturing fluid, primary and secondary fractures are distinguished, and the relationship between the number of fracture branches and the width, conductivity and pressure transmission of the main fracture is analyzed.

[0090] Statistical analysis module: evaluates the power law relationship between the number of microseismic events and the magnitude, counts the B values ​​of different well sections, and forms a systematic statistical analysis.

[0091] Event point separation module: Based on the energy-compensated microseismic information data, the separation scheme of microseismic event points is finally determined to achieve effective classification of natural fractures and reservoir matrix.

[0092] In another embodiment of the present invention, a terminal device is provided, the terminal device includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of the microseismic event point separation method.

[0093] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0094] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the microseismic event point separation method in the above embodiment; one or more instructions in the computer-readable storage medium are loaded and executed by the processor.

[0095] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the implementation methods of the present invention, and should be understood that the protection scope of the present invention is not limited to such special statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A microseismic event point separation method based on logging constraints, characterized in that: The following steps are involved: (a) Using well logging data, we analyze the energy differentiation characteristics of the well logging data curve and calculate the fracture strength curve as a condition constraint for subsequent microseismic data separation; (b) Extract the energy level, depth and spatial location information of microseismic event data and clarify the distribution law and characteristics of microseismic event points in three-dimensional space; (c) Based on the timing and spatial location of microseismic events, the fracture network morphology is constructed, assuming that new fractures are likely to extend from existing fractures; (d) Interactive analysis of the B value of microseismic events and the logging fracture intensity curve is performed, and energy compensation of microseismic energy levels is performed based on the fracture development intensity at different depths; (e) Based on the energy conservation principle of fracturing fluid, primary and secondary fractures are distinguished, and the relationship between the number of fracture branches and the width, conductivity and pressure transmission of the main fracture is analyzed; (f) Evaluate the power law relationship between the number of microseismic events and their magnitude, calculate the B values ​​of different well sections, and form a systematic statistical analysis; (g) Based on the energy-compensated microseismic information data, the separation scheme of microseismic event points is finally determined to achieve effective classification of natural fractures and reservoir matrix.

2. The method according to claim 1, characterized in that The calculation of the fracture strength curve is based on the anisotropic characteristics of the well logging data and the fracture porosity analysis.

3. The method according to claim 1, characterized in that The energy compensation is achieved by correcting the microseismic energy level.

4. The method according to any one of claims 1, characterized in that The power law relationship is derived by statistically analyzing the frequency and magnitude distribution of microseismic events, forming a linear model to support the prediction of microseismic events.

5. The method according to any one of claims 1, characterized in that The separation scheme has been verified many times, using different test data to ensure the accuracy and reliability of the results.

6. A microseismic event point separation system, characterized in that: The system can be used to implement the microseismic event point separation method according to any one of claims 1 to 5, specifically comprising: Data acquisition module: responsible for collecting well logging data and microseismic event data, including energy level, depth and spatial location information; Data preprocessing module: noise filtering, standardization and format conversion of the collected logging data and microseismic event data for subsequent analysis; Energy analysis module: Analyze the energy differentiation characteristics of logging data curves, calculate fracture strength curves, and provide conditional constraints for microseismic data separation; Spatial distribution analysis module: extract the spatial distribution law of microseismic events and construct the network morphology of microseismic events in three-dimensional space; Interactive analysis module: Interactive analysis of the B value of microseismic events and the logging fracture intensity curve, combined with the fracture development intensity at different depths, to perform energy compensation for the microseismic energy level; Primary and secondary fracture analysis module: Based on the energy conservation principle of fracturing fluid, primary and secondary fractures are distinguished, and the relationship between the number of fracture branches and the width, conductivity and pressure transmission of the main fracture is analyzed; Statistical analysis module: evaluates the power law relationship between the number of microseismic events and the magnitude, counts the B values ​​of different well sections, and forms a systematic statistical analysis; Event point separation module: Based on the energy-compensated microseismic information data, the separation scheme of microseismic event points is finally determined to achieve effective classification of natural fractures and reservoir matrix.

7. A computer device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the microseismic event point separation method described in one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the microseismic event point separation method described in one of claims 1 to 5 is implemented.

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