Connectivity quantitative characterization method, equipment, medium and product

Abstract

The invention discloses a connectivity quantitative characterization method, and relates to the technical field of geological structure and oil exploration, and the method comprises the steps: obtaining geological background data and seismic data of a to-be-characterized region; determining seismic analysis data of the to-be-represented area according to the geological background data and the seismic data; the seismic analysis data comprises structural map data, fracture geometric parameter data and kinematic parameter data; determining a sand box model of the sand box physical simulation experiment according to the geological background data and the seismic analysis data; after the physical simulation experiment of the sand box is finished, obtaining experimental data of the physical simulation experiment of the sand box; the experimental data comprises the anticline uplift amplitude and the anticline average slope angle under a plurality of horizontal displacement conditions; and carrying out quantitative characterization on the connectivity between the anticlines by using the anticline uplift amplitude and the anticline average slope angle. Only geological background data and seismic data are utilized for analysis, the cost is low, and the analysis process is objective.

Description

Technical Field

[0001] The present application relates to the field of geological structure and petroleum exploration technology, and in particular to a method, device, medium and product for quantitative characterization of connectivity. Background Art

[0002] Strike-slip faults are one of the three major types of faults. Strike-slip faults represented by the San Andreas Fault, North Anatolian Fault, Tanlu Fault, etc. all show important influences on the "storage, transportation, and accumulation" of oil and gas or the occurrence of earthquake disasters.

[0003] At present, researchers at home and abroad have carried out research on the characterization of small displacement strike-slip faults in the craton from multiple angles, such as well logging identification, seismic prediction, geological modeling and dynamic inversion, in order to characterize the three-dimensional spatial configuration of faults and reservoir connectivity, and have made many positive progress. However, due to the simultaneous development of pores, fractures and caves in such reservoirs and the large scale differences, it is difficult to use a unified method to characterize them, so the research on different types of reservoirs is often "separate", and their spatial correlation is difficult to reflect. Therefore, it is imperative to study the spatial distribution law of strike-slip faults and the coupling of connectivity.

[0004] Existing technologies mainly characterize reservoirs and connectivity through geophysical means, actual drilling and production data, etc. The geophysical means are mainly three-dimensional reservoir characterization technology, etc., through which reservoir connectivity can be carved, but this method can adjust parameters manually, which is too subjective, and also requires very accurate three-dimensional seismic data and logging data, etc. Actual drilling and production data refers to the underground structure obtained by oil and gas companies through drilling oil and gas wells. At the same time, through the analysis of oil and gas production, geochemical parameters, etc., it can be known whether the oil and gas wells are connected. However, this method requires a large amount of drilling data and is suitable for areas with deep exploration. It is not applicable to areas that have just started exploration, and this method will also increase production costs. Summary of the invention

[0005] The purpose of this application is to provide a method, device, medium and product for quantitative characterization of connectivity, which only uses geological background information and seismic data for analysis, has low cost and objective analysis process.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a method for quantitatively characterizing connectivity, the method comprising:

[0008] Obtain geological background information and seismic data for the area to be characterized;

[0009] Determine the seismic analysis data of the area to be characterized according to the geological background information and seismic data; the seismic analysis data includes: structural map data, fracture geometry parameter data and kinematic parameter data;

[0010] Determine a sand box model for a sand box physical simulation experiment according to the geological background information and the seismic analysis data;

[0011] After the sand box physical simulation experiment is completed, experimental data of the sand box physical simulation experiment is obtained; the experimental data includes: anticline uplift amplitude and anticline average slope angle under several horizontal displacement conditions;

[0012] The connectivity between the anticlines is quantitatively characterized using the anticline uplift amplitude and the anticline average slope angle.

[0013] Optionally, the experimental data also includes: sliding displacement and R rupture length; quantitatively characterizing the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle, specifically including:

[0014] According to the anticline uplift amplitude, sliding displacement and R rupture length, a quantitative model of the growth evolution process of the strike-slip fault is constructed;

[0015] According to the anticline uplift amplitude and the anticline average slope angle, a quantitative model of anticline connectivity is constructed; the quantitative model of anticline connectivity uses the anticline uplift amplitude and the anticline average slope angle to intuitively characterize whether anticlines are connected.

[0016] Optionally, determining the seismic analysis data of the area to be characterized according to the geological background information and seismic data specifically includes:

[0017] Determine the strike-slip fault data in the seismic data based on the geological background information and seismic data in combination with geological theory;

[0018] The seismic analytical data of the area to be characterized are determined according to the strike-slip fault data; the seismic analytical data specifically include: planar extension length data of the strike-slip fault zone, segmentation data, vertical fault distance data, fault penetration layer data, fault penetration stratum capability data and profile stratification data.

[0019] Optionally, determining a sand box model for a sand box physical simulation experiment according to the geological background information and the seismic analysis data specifically includes:

[0020] Determine the scale of the sandbox model according to the structural drawing data;

[0021] Determining the material and base conditions of the sandbox model according to the geological background data and the fracture geometry parameter data;

[0022] The force mode and constraint conditions of the sand box model are determined according to the geological background information and the kinematic parameter data.

[0023] Optionally, after the sand box physical simulation experiment is completed, experimental data of the sand box physical simulation experiment is obtained, specifically including:

[0024] After the sand box physical simulation experiment is completed, the experimental data of the sand box physical simulation experiment is obtained by using a camera and a laser scanner device.

[0025] Optionally, the connectivity between the anticlines is quantitatively characterized by using the anticline uplift amplitude and the anticline average slope angle, specifically including:

[0026] The connectivity between the anticlines is identified according to the uplift amplitude of the anticline; for the same strike-slip fault zone, when the uplift amplitude of the anticline is small, it means that the connectivity probability is large; when the uplift amplitude of the anticline is large, it means that the connectivity probability is small.

[0027] Optionally, after quantitatively characterizing the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle, the method further comprises:

[0028] Obtain attribute slice data and well logging data of the area to be characterized;

[0029] The R rupture length data is determined by combining the sandbox model, the attribute slice data, the seismic data and the well logging data.

[0030] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the above-described methods for quantitatively characterizing connectivity.

[0031] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for quantitatively characterizing connectivity.

[0032] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned quantitative connectivity characterization methods.

[0033] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0034] The present application provides a method for quantitative characterization of connectivity, which includes: obtaining geological background data and seismic data of the area to be characterized; determining seismic analytical data of the area to be characterized based on the geological background data and seismic data; the seismic analytical data includes: structural map data, fracture geometry parameter data and kinematic parameter data; determining a sandbox model of a sandbox physical simulation experiment based on the geological background data and the seismic analytical data; obtaining experimental data of the sandbox physical simulation experiment after the sandbox physical simulation experiment is completed; the experimental data includes: anticline uplift amplitude and anticline average slope angle under several horizontal displacement conditions; using the anticline uplift amplitude and the anticline average slope angle to quantitatively characterize the connectivity between the anticlines. The characterization method provided by the present application only uses geological background data and seismic data, does not require the acquisition of a large amount of drilling data, and does not require very accurate three-dimensional seismic data bodies and logging data, etc. Moreover, the present application does not require the reservoir connectivity to be carved by geophysical means, thereby making the analysis process more objective. The present application only uses geological background data and seismic data for analysis, which is low-cost and objective in the analysis process. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 This is an application environment diagram of a connectivity quantitative characterization method in one embodiment of the present application;

[0037] Figure 2 A schematic diagram of a method for quantitative characterization of connectivity provided in Example 1 of the present application;

[0038] Figure 3 A schematic diagram of a quantitative model for anticline penetration provided in Example 1 of the present application;

[0039] Figure 4 A schematic diagram of processing experimental scanning results using three-dimensional modeling software for characterizing the growth connection process and evaluating the connectivity of small-displacement strike-slip faults within a craton provided in Example 1 of the present application;

[0040] Figure 5 A schematic diagram of a method for quantitative characterization of connectivity provided in Example 2 of the present application;

[0041] Figure 6A schematic diagram of a method for calculating net deformation of a stratum for characterizing the growth connection process and evaluating the connectivity of small-displacement strike-slip faults within a craton provided in Example 2 of the present application;

[0042] Figure 7 TO for characterizing the growth connection process and evaluating the connectivity of small displacement strike-slip faults in the craton provided in Example 2 of the present application 3t Schematic diagram of connectivity determination of net deformation of reflective layer;

[0043] Figure 8 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] Since the 19th century, sandbox tectonic physical simulation experiments based on the principles of self-similarity and irrational effectiveness of geological tectonic processes can use small-scale models to simulate the deformation evolution process and dynamic mechanism of strike-slip fault tectonic systems. Cloos conducted the first simulation experiment of strike-slip tectonics in 1928, but the Riedel experiment is widely known. The Riedel experiment uses two steel plates to simulate a vertical basement strike-slip fault, covered with a certain thickness of wet clay as the initial undeformed cover layer, to simulate the deformation process of basement strike-slip fault propagation. Based on this experimental model, Naylor (1986) and others used quartz sand to conduct the same Riedel experiment. The above two experiments laid the foundation for the formation and evolution of strike-slip faults. The two experiments have similar evolution processes as a whole, and the associated structural types are slightly different in details. In general, strike-slip faults have two characteristics: ① Strike-slip faults have segmented combination characteristics, and with the increase of displacement, they eventually form a through-strike-slip zone. In actual exploration, segmented connection combination characteristics are generally reflected; ② En echelon faults (R ruptures) are the main product of strike-slip fault evolution, and their number is significantly greater than other strike-slip associated structures, which are of great research value. Direct observation and camera recording in sand box physical simulation experiments are the most commonly used means. With the advancement of computers, numerical CCD cameras and other technologies (such as CT, laser scanning technology, etc.), the movement laws of different pixels or dot arrays in the sand box model can be obtained with higher resolution. This application uses sand box physical simulation and other technologies to obtain the geometric and kinematic parameters of strike-slip faults, analyze the evolution process and connectivity of the faults, scientifically and rationally predict and comprehensively evaluate, reduce geological multi-solutions and exploration and development costs, and provide favorable targets for well site deployment. This application proposes a method for characterizing the growth and connection process of small-displacement strike-slip faults in the craton and evaluating their connectivity, which solves the technical problem of quantitative characterization of the growth evolution and spatial distribution law of strike-slip faults and their connectivity. By using three-dimensional seismic data, production data and sand box physical simulation experiments, the growth evolution process and planar connectivity of small-displacement strike-slip faults in the craton are quantitatively evaluated.

[0046] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0047] The quantitative characterization method of connectivity provided in the embodiments of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the geological background data and seismic data to be processed to the server 104. After the server 104 receives the geological background data and seismic data to be processed, it determines the seismic analysis data of the area to be characterized according to the geological background data and seismic data; the seismic analysis data includes: structural map data, fracture geometry parameter data and kinematic parameter data; the sand box model of the sand box physical simulation experiment is determined according to the geological background data and the seismic analysis data; when the sand box physical simulation experiment is completed, the experimental data of the sand box physical simulation experiment is obtained; the experimental data includes: the anticline uplift amplitude and the average slope angle of the anticline under several horizontal displacement conditions; the connectivity between the anticlines is quantitatively characterized by the anticline uplift amplitude and the average slope angle of the anticline. In addition, in some embodiments, the connectivity quantitative characterization method can also be implemented by the server 104 or the terminal 102 alone, such as the terminal 102 can directly process the geological background information and seismic data to be processed.

[0048] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0049] Embodiment 1:

[0050] In an exemplary embodiment, Figure 2 As shown, a method for quantitative characterization of connectivity is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S1 to S5. Among them:

[0051] S1. Obtain geological background information and seismic data for the area to be characterized.

[0052] S2. Determine the seismic analysis data of the area to be characterized according to the geological background information and seismic data; the seismic analysis data includes: structural map data, fracture geometry parameter data and kinematic parameter data.

[0053] Specifically: based on the geological background information and seismic data, combined with geological theory, the strike-slip fault data in the seismic data is roughly determined.

[0054] The seismic analytical data of the area to be characterized are determined according to the strike-slip fault data; the seismic analytical data specifically include: planar extension length data of the strike-slip fault zone, segmentation data, vertical fault distance data, fault penetration layer data, fault penetration stratum capability data and profile stratification data.

[0055] In this embodiment, geological background information and seismic data of the area to be characterized are obtained, and the strike-slip faults in the seismic data are preliminarily analyzed in combination with the regional geological background and geological theory, including the analysis of the planar extension length, segmentation, vertical fault throw, fault penetration layer and fault penetration stratum capability, profile stratification, etc. of the small-displacement strike-slip fault zone, so as to obtain preliminary structural maps and fault geometry and kinematic parameters of the study area.

[0056] First, the faults with obvious fault throws on the seismic profile are analyzed. After the obvious faults are analyzed, they are combined with the previous research results (literature) and analyzed with reference to the general characteristics of the evolution of strike-slip fault zones. That is, the strike-slip fault zone may have segmented characteristics and near-linear structures on the plane, and a flower-like structure on the profile. The three-dimensional display shows the visible ribbon effect and dolphin effect. Through this step, the fault type and development characteristics of the area to be characterized are roughly determined, and some parameters are obtained to guide the subsequent sand box physical simulation experiments.

[0057] S3. Determine a sand box model for a sand box physical simulation experiment according to the geological background information and the seismic analysis data.

[0058] Specifically: the scale of the sand box model is determined according to the structural map data; the material of the sand box model is determined according to the geological background data and the fracture geometry parameter data; the force mode and constraint conditions of the sand box model are determined according to the geological background data and the kinematic parameter data.

[0059] In this embodiment, based on the actual situation of the area to be characterized, a sand box model is designed, and a sand box physical simulation experiment is carried out to obtain experimental data:

[0060] The structural prototype is determined based on geological analysis, and then the main factors controlling the structural prototype are analyzed. The scale of the sand box model is determined according to the geometric dimensions of the prototype and the experimental method adopted, and suitable similar materials are selected according to the structural deformation conditions and the rock mechanical properties of the prototype. The loading mode and boundary geometric conditions of the sand box model are determined according to the prototype force mode and constraint conditions inferred from the analysis of geological and geophysical data, so that the sand box model reaches similarity with the actual geological conditions in geometry, kinematics, experimental materials and geological conditions; then, the substrate, quartz sand, silica gel and other experimental materials are laid and leveled on the sand box physical simulation experimental device, the monitoring equipment and experimental instruments are started, and the experimental process and parameters are recorded using cameras, laser scanners and other equipment.

[0061] S4. After the sand box physical simulation experiment is completed, experimental data of the sand box physical simulation experiment is obtained; the experimental data includes: anticline uplift amplitude and anticline average slope angle under several horizontal displacement conditions.

[0062] S5. Quantitatively characterize the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle.

[0063] The experimental data also include: sliding displacement and R rupture length; quantitative characterization of the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle, specifically including:

[0064] According to the anticline uplift amplitude, sliding displacement and R rupture length, a quantitative model of the growth evolution process of the strike-slip fault is constructed;

[0065] According to the anticline uplift amplitude and the anticline average slope angle, a quantitative model of anticline connectivity is constructed; the quantitative model of anticline connectivity uses the anticline uplift amplitude and the anticline average slope angle to intuitively characterize whether anticlines are connected.

[0066] In this embodiment, experimental data analysis is performed to quantitatively characterize the growth evolution process of the strike-slip fault, and at the same time, the faults and strata of the strike-slip fault zone are finely analyzed by combining experimental results, outcrop analysis, well logging, 3D seismic and other data.

[0067] Using the experimental parameters recorded by multiple sets of sandbox physical simulation experiments, the geometric and kinematic parameters such as fault throw, anticline uplift amplitude, and number of faults are read, and the parameters such as anticline uplift amplitude, sliding displacement, and R rupture length are selected to establish a quantitative model of the growth and evolution process of strike-slip faults. At the same time, the growth and evolution process of strike-slip faults has similarities. The sandbox physical simulation experiment can represent the formation and evolution history of natural strike-slip fault zones to a certain extent. Based on the sandbox model, attribute slices, 3D seismic, logging and other data of the sandbox physical simulation experiment, the 3D seismic faults and strata are finely analyzed.

[0068] Among them, the attribute slice is calculated in the software based on the three-dimensional seismic data, the purpose is to roughly determine the plane characteristics of the fault; the three-dimensional seismic and logging data are provided by the company; after the experiment is completed, the results can be obtained through analysis by the net deformation method, and the results can show that the development location of the R rupture is located between the two anticlines. According to this method, the R rupture can be drawn at the relevant position of the earthquake. The purpose of this fine analysis process is not to identify obvious faults, but to identify this difficult-to-distinguish R rupture. The result of the analysis is that a growth evolution model of the strike-slip fault zone is established through sandbox physical experiments, and earthquakes are analyzed according to this model, and finally the difficult-to-identify R rupture is explained.

[0069] Then, according to the quantitative model of the growth evolution process of strike-slip faults and production data, the control factors are optimized, the characterization parameters are selected, and the method model of the continuity of strike-slip faults is established using parameters such as the anticline uplift amplitude and the average slope angle of the anticline, such as Figure 3 shown.

[0070] Among them, the relationship between the evolution degree of the fault zone and connectivity is analyzed according to the quantitative model of the growth evolution process of the strike-slip fault and the results of fine structural analysis, that is, the uplift amplitude of the anticline in the strike-slip fault zone is the key parameter for identifying connectivity. When the uplift amplitude of the anticline is small, it means that the strike-slip fault zone is more likely to penetrate and is connected to the adjacent anticline; when the uplift amplitude of the anticline is large, it means that the strike-slip fault zone is less likely to penetrate and will not penetrate the adjacent anticline. At the same time, using production and other data, comprehensively analyzing the oil pressure drop and production difference between different wells in the fault zone, and combining the three-dimensional carving results of the reservoir, etc., further optimize the connectivity identification and determine the minimum penetration amplitude. The optimization method is to use the research results of predecessors, that is, the three-dimensional carving results of the reservoir, the oil pressure drop between wells, the production difference, etc., to adjust the development position of the R fracture; the optimization process is to refer to the three-dimensional carving results of the reservoir, the oil pressure drop between wells, the production difference, etc. made by predecessors to correct the analytical results of this embodiment. Because the geological body is complex, the analysis of this embodiment is not 100% correct and may be affected by the local stress field. Subsequently, the structural related characterization parameters (anticline uplift amplitude and anticline average slope angle, etc.) were optimized to establish a method model for the continuity of strike-slip faults (quantitative model for anticline continuity). This model can effectively indicate whether the strike-slip fault zone is connected in this section of the reservoir by using the anticline uplift amplitude and anticline average slope angle, thereby guiding well site deployment and later fracturing development.

[0071] In brief, this embodiment mainly uses the average slope of the anticline and the anticline uplift amplitude parameters for quantitative characterization and evaluation. The characterization and evaluation result is that three categories are divided, namely connected, disconnected, and possibly connected.

[0072] This embodiment is based on geological theory. Based on the results of detailed analysis of three-dimensional seismic data, the strike-slip faults in the M area of ​​the Tarim Basin are taken as the research object. Sand box physical simulation experiments and numerical CCD cameras, laser scanners and other equipment are used to obtain the geometric and kinematic parameters of strike-slip faults, establish a quantitative characterization method for the growth and evolution of strike-slip faults, and at the same time, combine actual production data to establish a method model for the connectivity of strike-slip faults. This method solves the technical problem of quantitative characterization of the growth and evolution of strike-slip faults and their spatial distribution laws-connectivity, and provides a technical method for quantitative research on the formation and evolution of small-displacement strike-slip faults in the craton, oil and gas transportation, and reservoir control. The schematic diagram of the experimental scanning result processing is shown in the figure. Figure 4 shown.

[0073] Embodiment 2:

[0074] In an exemplary embodiment, Figure 5 As shown, a method for quantitative characterization of connectivity is provided, comprising the following steps:

[0075] Step A1, there are many strike-slip faults in the M area of ​​the Tarim Basin. These small-scale strike-slip faults have the characteristics of "south-north segmentation, east-west division, vertical stratification, and multi-stage activity superposition". At the same time, these strike-slip faults have obvious "control of storage, reservoir, and richness" effects on the carbonate rocks developed in the Ordovician. Many exploration wells located on strike-slip faults have also made major exploration breakthroughs. Using the research results of predecessors and logging data, the stratigraphic position of the strata near the strike-slip fault zone in the seismic data was calibrated, and the strike-slip fault was preliminarily interpreted in combination with the geological model to obtain preliminary seismic interpretation results. Based on the preliminary fault interpretation results, preliminary structural maps of the study area and fault geometry and kinematic parameters were obtained, and the geological model of the M area was clarified.

[0076] Step A2, strike-slip faults are developed in the M area of ​​the Tarim Basin, and they are all small-displacement strike-slip faults. It is difficult to identify the structural style and tiny structures of strike-slip faults on the seismic profile. The sand box physical simulation experiment is used to observe the overall evolution process of strike-slip faults at the laboratory scale, so as to understand the geometric and kinematic characteristics of the development of strike-slip faults under different horizontal displacements. A simple shear experiment series is set up. Simple shear strike-slip faults generally develop from the basement to the upper cover layer. Two adjacent rigid basement plates are used to simulate upright and straight basement strike-slip faults. White quartz sand is covered on the basement plate to simulate the overlying layer. The sand body particle size range is 80-120 mesh, which is consistent with the material similarity. At the same time, according to the actual situation in nature, the sand body thickness is calculated to be T = 4cm according to the principle of geometric similarity. The experiment drives the basement plate to shear by driving the push plate displacement by a motor. During the process, as the motor continues to push, the strike-slip displacement gradually increases, and the sand body is 3D scanned and photographed from a bird's-eye view. Use drawing, 3D modeling and other software to collect horizontal and vertical break distances, break lengths and other data from 3D scanning coordinate data and photos. Use the collected data to draw, analyze its existence patterns, summarize and other work.

[0077] Step A3, the results of the simple shear sand box physical simulation experiment are as follows: in the early stage of the evolution of the strike-slip fault zone, the experimental displacement is accumulated, the marker line is significantly bent, but no obvious rupture occurs, the strain is regulated by the sliding rearrangement of the particles, and the fault gradually propagates from the base to the surface at this stage. Until the experimental displacement reaches 6.5 mm, a shear zone is generated, and the initial position of the "R rupture" is strained. The strike-slip direction is consistent with the base shear direction, and the strike-slip fault zone is confined to a certain width. As the strike-slip displacement increases, the shear zone expands along the strike and swings in a direction more parallel to the basement fault trajectory. As the experiment continues, P rupture occurs, and stress gradually concentrates on the P rupture. At this time, the early R rupture no longer develops. Finally, a series of Y shear ruptures are connected to form a shear zone that runs through the strike-slip fault zone. The early formed fault segment is no longer developed, and the basement strike-slip displacement is concentrated on the shear zone that runs through it, that is, the main displacement zone (PDZ).

[0078] Then, the 3D scanning coordinate data and 3D modeling software (such as SURFER, PETTREL, etc.) are used to quantitatively analyze the strike-slip fault. The laser scanning (xyz format data) digitization experimental results are as follows: Figure 6As shown. The scanning results are displayed as "points" in the modeling software. Each data point has x, y, and z values. At the same time, the data points can be optimized and identified by adjusting the color scale of the 3D modeling software. By clicking each point in the 3D modeling software with the mouse, the vertical fault distance and uplift height of the sand body fault can be read. At the same time, the fault length of each fault can be read using measurement tools. The same fault is measured multiple times and the average value is taken to eliminate the error. Due to modeling errors or experimental errors, the 3D model of the sand body may be tilted. When measuring the uplift height, the average value of the five values, the z value of the four corners and the z value of the center, is used as the plane height to eliminate the error. When measuring the vertical fault distance, the distance between the low point and the high point used is very close, and there is almost no error, so there is no need to eliminate the error. When measuring the length of the fault, the trigonometric function calculation can be performed based on the obtained x and y values ​​of the two end points of the fault to obtain the fault length.

[0079] Based on the qualitative analysis of the comprehensive photos and the quantitative analysis of the three-dimensional modeling, it is not difficult to conclude that in the early stage of the experiment, the "R ruptures" arranged in en echelon appeared first, and their horizontal fault throw, vertical fault throw and fault length developed slowly. When the "R ruptures" were about to be dislocated and stopped developing, the "PDZ ruptures" gradually appeared. That is, as the displacement gradually increased, the "R ruptures" gradually spread, generating a small number of new "PDZ ruptures". The "PDZ ruptures" were formed between the two overlapping "R ruptures" and intersected with the basement fault trace at a low angle. Their development speed, especially the horizontal fault throw and fault length, were significantly greater than that of the "R ruptures", and their development time span was long until the strike-slip zone was completely connected. As the strike-slip displacement increased, the "R ruptures" and "PDZ ruptures" were connected to form an interwoven strike-slip zone and a shear lens, with an angle nearly parallel to the pre-existing fault trace of the basement. According to the above analysis, a quantitative characterization chart of the growth and evolution process of strike-slip faults was established.

[0080] At the same time, from the 3D scanning coordinate data of the physical simulation experiment of the strike-slip fault sand box, it can be seen that the development of the R shear fault has a very clear correlation with the anticline. The R shear fault develops at the part with the highest formation dip angle on the entire anticline, that is, the formation dip angle suddenly becomes steep. Based on this feature, the target fault zone in the M area is finely analyzed. Even though the low seismic resolution has a certain "smoothing" phenomenon, the R shear fault can still be identified.

[0081] Step A4, in step S3, the process and quantitative characterization parameters of the growth evolution of the strike-slip fault were discussed. It was found that in the simple shear process, the R rupture was formed first, accompanied by the uplift and downfall of the surface strata. As the strike-slip displacement gradually increased, the P rupture and PDZ began to form, and the R rupture stopped growing, and the uplift amplitude did not increase much. On this basis, 3D laser scanning was used to scan the surface of the simple shear sand box physical simulation experiment, with an experimental displacement of 1mm as an interval, and then the particles were analyzed and calculated to calculate the vertical deformation increment, and the vertical deformation law of each evolution stage was finely characterized to identify the continuity of the strike-slip fault. The 3D scanning results of the two adjacent groups of experiments were subtracted to obtain the control degree of each 1mm strike-slip displacement on the experimental surface, that is, whether the strata were uplifted, downfall or displacement. When the experimental displacement was 6-9mm, the PDZ was not connected, and only the R rupture developed. At this time, the deformation increment between 6-9mm showed that the entire strike-slip fault formed an uplift between the two R ruptures, and the deformation was not obvious at the development of the R rupture. When the experimental displacement is 10-13 mm, the PDZ gradually develops, but is not fully connected. At this time, the deformation increment finds that the anticline uplift trend weakens. When the experimental displacement is 14-19 mm, the PDZ is fully connected. At this time, the deformation increment finds that the anticline is no longer uplifted. That is, in high-amplitude deformation areas, the probability of connection between regions is low, and the probability of reservoir connection in low-amplitude deformation areas is high.

[0082] Combining the geological model and the results of the sandbox physical simulation experiment, when analyzing the activity of the strike-slip fault growth process, it is necessary to eliminate the stratum deformation around the strike-slip fault and obtain the relative stratum uplift and downfall. The calculation method of the stratum net deformation is as follows: Figure 6 First, we interpret the earthquake in detail and derive xyz data. Then, we select a relatively flat area in Shuanghuli, delete the strata in the middle fault zone and the deformation zone, and then interpolate the layers, subtracting the original layers from the interpolated trend surface.

[0083] Based on the data of sand box physical simulation experiment, the anticline uplift amplitude and the average slope angle α of the anticline (average slope of the anticline = uplift height / 0.5 anticline width, i.e. tanα) were used to establish a discriminant chart of the growth stage of the strike-slip fault in the compression-torsion zone. The calculation of the net deformation showed that there were 7 obvious local highs in the southern section of the strike-slip fault zone in the M area, and 3 obvious local highs in the middle section, such as Figure 7 As shown in FIG. 1 , through quantitative analysis of the uplift amplitude and the average slope angle of the anticline, it is known that the uplift amplitude of the anticline at the local high positions of No. 6, No. 8, No. 9, and No. 10 is small, the average slope of the anticline is small, the PDZ is formed earlier, the fault transformation is strong, and the probability of penetration is high; the uplift amplitude of the anticline at the high position of No. 2 is large, the average slope of the anticline is large, the PDZ is formed later, most of the displacement is absorbed by the uplift belt, and the probability of penetration is low, as shown in Example 1. Figure 3As shown (it can also be understood as a growth stage discrimination chart for compression-torsion strike-slip faults for characterizing the growth connection process and evaluating the connectivity of small-displacement strike-slip faults within the craton). At present, the prediction results of this embodiment are consistent with the results of production data, well-to-well connectivity surveys, etc., which illustrates the reliability of this method.

[0084] In summary, the present invention provides a method for characterizing the growth connection process and evaluating the connectivity of small displacement strike-slip faults within the craton, using sandbox physical simulation experiments and net deformation to analyze the fault evolution process and connectivity, making the fault characterization and reservoir description more refined. The present invention can describe the three-dimensional spatial configuration and planar connectivity of strike-slip faults in the actual exploration process, scientifically and rationally predict and comprehensively evaluate, reduce geological multi-solutions and exploration and development costs, and provide favorable targets for well site deployment.

[0085] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for quantitative characterization of connectivity is implemented.

[0086] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0087] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0088] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0089] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0090] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0091] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0092] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0093] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for quantitative characterization of connectivity, characterized in that: The connectivity quantitative characterization method comprises: Obtain geological background information and seismic data for the area to be characterized; Determine the seismic analysis data of the area to be characterized according to the geological background information and seismic data; the seismic analysis data includes: structural map data, fracture geometry parameter data and kinematic parameter data; Determine a sand box model for a sand box physical simulation experiment according to the geological background information and the seismic analysis data; After the sand box physical simulation experiment is completed, experimental data of the sand box physical simulation experiment is obtained; the experimental data includes: anticline uplift amplitude and anticline average slope angle under several horizontal displacement conditions; The connectivity between the anticlines is quantitatively characterized using the anticline uplift amplitude and the anticline average slope angle.

2. The method for quantitative characterization of connectivity according to claim 1, characterized in that: The experimental data also include: sliding displacement and R rupture length; quantitative characterization of the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle, specifically including: According to the anticline uplift amplitude, sliding displacement and R rupture length, a quantitative model of the growth evolution process of the strike-slip fault is constructed; According to the anticline uplift amplitude and the anticline average slope angle, a quantitative model of anticline connectivity is constructed; the quantitative model of anticline connectivity uses the anticline uplift amplitude and the anticline average slope angle to intuitively characterize whether anticlines are connected.

3. The method for quantitative characterization of connectivity according to claim 1, characterized in that: Determining the seismic analysis data of the area to be characterized according to the geological background information and seismic data specifically includes: Determine the strike-slip fault data in the seismic data based on the geological background information and seismic data in combination with geological theory; The seismic analytical data of the area to be characterized are determined according to the strike-slip fault data; the seismic analytical data specifically include: planar extension length data of the strike-slip fault zone, segmentation data, vertical fault distance data, fault penetration layer data, fault penetration stratum capability data and profile stratification data.

4. The method for quantitative characterization of connectivity according to claim 1, characterized in that: Determining a sand box model for a sand box physical simulation experiment based on the geological background information and the seismic analysis data specifically includes: Determine the scale of the sandbox model according to the structural drawing data; Determining the material of the sandbox model according to the geological background information and the fracture geometry parameter data; The force mode and constraint conditions of the sand box model are determined according to the geological background information and the kinematic parameter data.

5. The method for quantitative characterization of connectivity according to claim 1, characterized in that: After the sand box physical simulation experiment is completed, experimental data of the sand box physical simulation experiment is obtained, specifically including: After the sand box physical simulation experiment is completed, the experimental data of the sand box physical simulation experiment is obtained by using a camera and a laser scanner device.

6. The method for quantitative characterization of connectivity according to claim 1, characterized in that: The connectivity between the anticlines is quantitatively characterized by using the anticline uplift amplitude and the anticline average slope angle, specifically including: The connectivity between the anticlines is identified according to the uplift amplitude of the anticline; for the same strike-slip fault zone, when the uplift amplitude of the anticline is small, it means that the connectivity probability is large; when the uplift amplitude of the anticline is large, it means that the connectivity probability is small.

7. The method for quantitative characterization of connectivity according to claim 1, characterized in that: After quantitatively characterizing the connectivity between the anticlines using the anticline uplift amplitude and the anticline average slope angle, the method further includes: Obtain attribute slice data and logging data of the area to be characterized; The R rupture length data is determined by combining the sandbox model, the attribute slice data, the seismic data and the well logging data.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the connectivity quantitative characterization method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the connectivity quantitative characterization method according to any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the connectivity quantitative characterization method according to any one of claims 1 to 7 is implemented.

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