CN114114411A - Quantitative determination method and device for three-dimensional fault conductibility - Google Patents
Quantitative determination method and device for three-dimensional fault conductibility Download PDFInfo
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Abstract
The invention provides a quantitative determination method and a quantitative determination device for three-dimensional fault conductances, wherein the method comprises the following steps: acquiring section data and horizon data according to the three-dimensional seismic data after the study area is overlapped; establishing a three-dimensional geological model according to the section data, the horizon data and the logging information; performing gridding processing on a section in the three-dimensional geological model to obtain a grid model; obtaining the thickness of a mudstone layer in each grid point in the section of the grid model and the displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in the grid points along the actual smearing displacement of the section; calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section; and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed. The invention can quantitatively analyze the three-dimensional fault conductivity and has high accuracy.
Description
Technical Field
The invention relates to the technical field of oil-gas exploration and development, in particular to a quantitative determination method and device for three-dimensional fault conductivity.
Background
In the practice of exploration and development of a fault block oil and gas reservoir, the fault can play a role in sealing oil and gas and also can play a role in dredging oil and gas, and the unsealed fault can enable the oil and gas to pass through to form lateral migration of the oil and gas to form the reservoir.
The research on the sealing performance of the fault is an opposite face and a key point of the research on the persuasion of the fault, and the research on the sealing performance of the fault is a difficult problem which puzzles oil and gas geologists. Fault closure is bidirectional, i.e. vertical and lateral closure. The fault sealing performance is evaluated by screening a plurality of variables which have large influence on the sealing or opening of the fault in the region on the basis of well-known fault characteristics of the research region, closely combining a correct fault sealing mechanism, utilizing various accurate geological and geophysical data which are mastered and selecting a proper evaluation method for calculation and analysis, so that the objective and actual sealing of the fault in the region is reflected to the greatest extent by the evaluation effect. Many scholars consider fault closure to be based mainly on the lithology opposition of reservoirs and non-reservoirs; (ii) physical properties of the filler in the fracture zone. The early fault closure mechanism studies hypothesized that smearing of clay-rich layers along the fault plane can produce hypotonic fault mud in two reservoirs. Recent studies have shown that similar clay smear or fault muds are ubiquitous in near-shore deepwater zones blocking fault planes of oil and gas accumulation. In recent years, a clay smearing method, particularly a fault mud ratio (SGR) method is used for evaluating and predicting fault closure of a thick-layer clastic rock sequence region, and a lot of works are done by many scholars at home and abroad, so that great progress is made; since then, most foreign scholars have devoted themselves to study the features of faults, and quantitative evaluation methods for fault closure are rare.
In summary, considering the existing method for determining fault conductivity, the plugging property of a fault is usually analyzed first, the plugged fault cannot conduct oil and gas, the fault that is not plugged can conduct oil and gas, an oil and gas seepage channel is formed, and oil and gas are transported to a fault tray pair across the fault, so that two problems exist in the fault analysis process. The first is that: in most conventional methods for determining the sealing performance, the sealing performance is determined by an SGR fault mud ratio method. When the SGR method is specifically implemented, the thickness and the fault distance of mudstone of a fault disc are only related, factors such as lithological influence, section compaction and closing degree of the fault disc and actual smearing displacement change of the mudstone are not considered, and therefore the accuracy of determining the sealing performance is not high. Secondly, to evaluate the fault dredging capability, analysis closure is firstly performed, the process is complex, direct and quantitative parameters and calculation methods for evaluating the fault dredging capability are not available, and the evaluation efficiency is low. The calculated result is easy to deviate and mislead, so that exploration loss is caused due to incomplete analysis of the closure of the broken block.
Therefore, a quantitative determination method of fault dispersion is lacking at present.
Disclosure of Invention
The embodiment of the invention provides a quantitative determination method of three-dimensional fault conductivity, which is used for quantitatively analyzing the three-dimensional fault conductivity and has high accuracy and comprises the following steps:
acquiring section data and horizon data of a research area according to the post-stack three-dimensional seismic data of the research area;
establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area;
performing gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
obtaining the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section;
and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed.
The embodiment of the invention provides a quantitative determination device for three-dimensional fault conductivity, which is used for quantitatively analyzing the three-dimensional fault conductivity and has high accuracy, and the device comprises:
the data acquisition module is used for acquiring section data and layer data of the research area according to the post-stack three-dimensional seismic data of the research area;
the three-dimensional geological model establishing module is used for establishing a three-dimensional geological model according to the section data, the layer data and the logging information of the research area;
the grid model obtaining module is used for carrying out gridding processing on the section in the three-dimensional geological model to obtain a grid model;
the first calculation module is used for acquiring the thickness of the mudstone layer in each grid point in the section of the grid model, the actual mudstone smearing displacement on the section and depth data, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
the second calculation module is used for calculating a three-dimensional fracture surface dredging coefficient according to the mudstone distribution thickness and the fracture surface pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface;
and the dispersion determination module is used for determining the dispersion of the three-dimensional fault in the research area when the dispersion coefficient of the three-dimensional section is larger than the threshold value of the dispersion coefficient of the three-dimensional section, and otherwise determining that the three-dimensional fault in the research area is not dispersed.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the above quantitative determination method for three-dimensional fault canalization.
An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program for executing the above quantitative determination method of three-dimensional fault canality.
In the embodiment of the invention, the section data and the horizon data of the research area are obtained according to the post-stack three-dimensional seismic data of the research area; establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area; performing gridding treatment on the section in the three-dimensional geological model to obtain a grid model; obtaining the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section; calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section; and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed. In the process, the three-dimensional seismic data and the logging information of the study area after the superposition are comprehensively considered, the three-dimensional geological model is finally established, after the grid model is obtained, the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement along the section are quantitatively obtained, and then the three-dimensional section dredging coefficient is quantitatively calculated, so that the process of judging whether the three-dimensional fault in the study area is dredged or not according to the three-dimensional section dredging coefficient is more accurate.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for quantitative determination of three-dimensional fault conductance in an embodiment of the present invention;
FIG. 2 is a schematic diagram of the displacement of actual mudstone smear on a cross section in an embodiment of the invention;
FIG. 3 is a detailed flowchart of a method for quantitatively determining three-dimensional fault sparsity according to an embodiment of the present invention;
FIG. 4 is a schematic illustration of a three-dimensional geological model in an embodiment of the present invention;
FIG. 5 is a schematic illustration of a lithology curve chart in an embodiment of the invention;
FIG. 6 is a diagram of a relationship between a three-dimensional cross-section dispersion coefficient and a depth according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of an apparatus for quantitative determination of three-dimensional fault canalization in accordance with an embodiment of the present invention;
FIG. 8 is a diagram of a computer device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the embodiments is for illustrative purposes to illustrate the implementation of the present application, and the sequence of steps is not limited and can be adjusted as needed.
Fig. 1 is a flowchart of a method for quantitatively determining three-dimensional fault sparsity according to an embodiment of the present invention, as shown in fig. 1, the method includes:
102, establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area;
103, carrying out gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
104, acquiring the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
105, calculating a three-dimensional fracture surface dredging coefficient according to the mudstone distribution thickness and the fracture surface pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface;
and 106, when the three-dimensional section dispersion coefficient is larger than the threshold value of the three-dimensional section dispersion coefficient, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed.
In the method provided by the embodiment of the invention, the three-dimensional seismic data and the logging information after the study area is overlapped are comprehensively considered, the three-dimensional geological model is finally established, after the grid model is obtained, the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement along the section are quantitatively obtained, and then the three-dimensional section dredging coefficient is quantitatively calculated, so that the process of judging whether the three-dimensional section in the study area is dredged or not according to the three-dimensional section dredging coefficient is more accurate.
In step 101, acquiring section data and layer data of a research area according to the post-stack three-dimensional seismic data of the research area, specifically loading the post-stack three-dimensional seismic data of the research area into special seismic interpretation software Landmark or Geoeast, and interpreting a section and a target stratum to obtain elements such as total section distance, dip angle, strike direction and the like of the section, and obtaining elements such as layer thickness, dip angle and the like of the stratum. The existing method obtains section data and horizon data, and then determines fault closure to analyze conductances, most of the methods use drilling data, and the drilling position is required to be close to a target fault. Because the drilling data generally has two-dimension, when the existing method utilizes the drilling data to analyze and process, only simple two-dimension data calculation and analysis can be performed frequently, and three-dimension analysis cannot be performed. In contrast, the analysis process is limited in scope and does not meet the actual drilling needs well. The three-dimensional seismic data used in the embodiments of the present invention satisfy the need for three-dimensional analysis.
In step 102, a three-dimensional geological model is built according to the section data, the horizon data and the logging information of the research area, and in an embodiment, the building of the three-dimensional geological model according to the section data, the horizon data and the logging information includes:
establishing a horizon model according to the horizon data;
establishing a fault model according to the section data;
correcting the horizon model and the fault model based on the logging information;
and processing the connection relation between the horizon and the section according to the corrected horizon model and the corrected section model to form a three-dimensional geological model containing the horizon and the section.
In specific implementation, in order to establish a structural level model of each destination level according to the interpreted level data, in specific implementation, a structural model of a key plane is established in the structural level modeling (the key plane refers to a plane with more data information and capable of accurately establishing the structural level, such as oil group in a research area).
In one embodiment, building a horizon model from the horizon data includes:
s1: constructing a horizon structural surface model according to the horizon data;
loading the prepared layer bit data into professional modeling software such as a petrol or a GPTmodel, and constructing a layer structure surface model according to a kriging difference value, a least square method and the like; the geological conditions such as stratum degradation and the like can be processed according to the contact relation of the bedding surface; the method can use the result data of seismic interpretation or other software as constraint conditions, can generate a stratum body model firstly, and simultaneously establish a small-layer structural layer model under the constraint of a key layer; then, each small layer is vertically subdivided according to the requirement.
S2: and analyzing the relation between upper and lower adjacent levels in the level structure surface model in the three-dimensional space, and eliminating level distortion points causing series or cross to obtain a new level structure surface model.
S3: and smoothing the new horizon structural surface model to obtain a horizon model, wherein the smoothing times can be set according to the research precision requirement.
In specific implementation, the key of fault model construction is that the topological relation, the geometric characteristics and the attribute characteristics among all faults are visually expressed, the faults are taken as the boundaries of stratigraphic units, and a fault model is constructed; the fault data model is constructed by using profile data and a section method, a fault plane is constructed based on contour line reconstruction, a small fault plane is constructed based on the dip angle and the dip angle of an oil fault plane, a plurality of fault planes are used for constructing the fault model, and the fault data model capable of solving the problems is realized for spatial Changsha county, spatial calculation, spatial analysis and the like of the model. In specific implementation, the method can be carried out according to the following steps:
in one embodiment, establishing a fault model based on the profile data includes:
s1: removing malformed data points in the section data to obtain ridge breaking data, wherein the ridge breaking data comprises fault line data and fault point composition data;
and loading the interpreted fault data into professional modeling software such as petrol or GPTmodel, analyzing the fault data under a three-dimensional window, selecting a range to be modeled, and removing malformed data points, wherein the specific data format comprises Irap, Zmap, CPS-3 and the like.
S2: generating a fault plane model according to the fault ridge data;
specifically, a fault plane model can be generated by using a kriging difference value method and the like.
S3: analyzing the cross-over relation of the fault plane in the fault plane model, correcting the part of the fault plane model which does not meet the preset requirement to obtain the fault model, wherein the preset requirement comprises geological rules and characteristics, and the correction can be carried out in an editing mode.
In one embodiment, correcting the horizon model and the fault model based on the logging information includes:
s1: acquiring data of an aboveground layered system according to the logging information;
according to regional geological knowledge and well logging information, an aboveground layered system can be established, and aboveground layered system data can be obtained, wherein the name of the layered system is consistent with the name of an earthquake upper layer.
S2: and correcting the horizon model by using the data of the underground layered system to obtain the corrected horizon model, so that the horizon model and the underground layered system tend to be consistent, and the distribution of the horizon structure morphology is more consistent with the real geological condition.
S3: and correcting the fault model by using the corrected horizon model, wherein the horizon model can be synchronously edited during correction, so that the horizon model and the fault model are better matched, and the modeling precision and quality are improved.
In step 103, performing gridding processing on the section in the three-dimensional geological model to obtain a grid model, where the grid size may be set according to the research precision requirement, and the gridding section model may specifically be:
s1: and preliminarily selecting the section range needing gridding according to the research requirement and the section-layer connection relation.
S2: the type of mesh is selected according to the cross-sectional geometry, such as a triangular mesh or a rectangular mesh.
S3: and gridding the spatial section distribution of the target fault, wherein parameters such as gridding step length, grid size and the like can be set according to actual research needs, such as 4m multiplied by 4 m.
Particularly, in order to improve the grid quality, in the gridding process, the main direction of the grid selects the trend direction of the section, and the local area of the section can be subjected to grid encryption for meeting the precision requirement.
In an embodiment, the method further comprises:
and calculating the actual mudstone smearing displacement on the fracture surface in each grid point according to the dip angle and the fault distance in each grid point.
Fig. 2 is a schematic diagram of the displacement of the actual mudstone smear on the fracture surface in the embodiment of the present invention, and the following formula may be adopted to calculate the displacement of the actual mudstone smear on the fracture surface in each grid point according to the dip angle and the fault distance in each grid point:
Si＝Di/sina
wherein S isiThe displacement of actual mudstone smearing on the section in the ith grid point is obtained; diIs the ith netThe unit of the break distance in the grid points is cm; a is the tilt angle in the ith grid point.
In an embodiment, the method further comprises:
acquiring formation lithology data of the research area according to the logging information of the research area;
and obtaining the thickness of the mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum.
In one embodiment, the logging information includes at least one of shale content data, gamma data, sonic data, and resistivity data.
In the above embodiment, the formation lithology data includes formation lithology, the formation lithology of the research area may be calibrated by logging information of the research area, and specifically, the method includes loading a las-format logging curve into professional logging interpretation software, geo or other software, where the las-format logging curve includes a shale content curve, a gamma curve, an acoustic curve and a resistivity curve.
In one embodiment, the formation lithology of the research area may be calibrated according to a shale content curve and a gamma curve, and specifically includes: determining a shale content discrimination value and a gamma discrimination value of the sandstone according to the response characteristics of the sandstone and the mudstone in the research area, wherein the part of the research area, which is larger than the shale content curve, of the sandstone and the mudstone content data is larger than the shale content discrimination value, and the part of the gamma curve, which is larger than the gamma discrimination value, of the mudstone represents that the mudstone content is high, and the part of the research area is calibrated to be the mudstone; otherwise, the information is calibrated to be sandstone, so that the lithology information of the stratum in the whole research area is obtained.
In other embodiments, lithology calibration can be performed by using other curves to obtain lithology information. For example, the gamma curve and the resistivity curve are used for calibration, according to the sand-shale response characteristics of the research area, the part, in the gamma curve of the research area, of which the gamma data is smaller than the gamma discrimination value and the resistivity data is larger than the resistivity discrimination value is calibrated as sandstone, and otherwise, the part is calibrated as mudstone, so that the lithology information of the stratum of the whole research area is obtained.
And then, obtaining the thickness of the mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum, particularly, after the lithological data of the stratum in the grid points are loaded, if the thickness of the mudstone layer is larger than the size of the grid, the whole grid point is the mudstone, the thickness of the mudstone layer is not only the size of the fault distance in the longitudinal direction, but also the operation is carried out according to the actual thickness of the mudstone layer if the thickness of the mudstone layer is smaller than the size of the fault distance in the longitudinal direction.
And the depth data in each grid point can be directly read out from the section data with the depth according to the spatial fault distribution of the gridded target fault.
In one embodiment, the method for calculating mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual section smearing displacement includes the following steps:
the method comprises the following steps of calculating the mudstone distribution thickness of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface according to the thickness of the mudstone layer in each grid point in the fracture surface of the grid model and the actual mudstone smearing displacement on the fracture surface by adopting the following formula:
Li＝Hi/Si
wherein L isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; hiThe thickness of the mudstone layer in the ith grid point is shown; siThe displacement of actual mudstone smearing on the section;
calculating the section pressure at each grid point from the depth data at each grid point using the following formula:
Pi＝10-3Mi(ρl-ρw)·g·cosa
wherein, PiThe section pressure in the ith grid point is taken as the pressure; miDepth data in the ith grid point; rholIs the average density of the overburden; rhowIs the average density of formation water; g is the acceleration of gravity; a is the tilt angle in the ith grid point.
In the embodiment, since the hydrostatic pressure above the fault does not act on the fault, the pressure applied to the fault to promote healing of the fault is mainly the pressure generated by the gravity of the rock skeleton of the overlying strata, the average density of the overlying strata is obtained from the logging data near the fracture zone, and the average density of the formation water is obtained from the testing data.
In one embodiment, the three-dimensional fracture dredging coefficient is calculated according to the mudstone distribution thickness and the fracture pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture by adopting the following formula:
wherein C is a three-dimensional section dredging coefficient; l isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; piThe section pressure in the ith grid point.
The three-dimensional section dispersion coefficient of the whole section is obtained, and the dispersion coefficient of each grid point can also be obtained, so that a dispersion coefficient chart is formed and is convenient to observe.
In step 106, when the three-dimensional cross section dispersion coefficient is greater than the threshold value of the three-dimensional cross section dispersion coefficient, determining the three-dimensional cross section dispersion of the study region, otherwise, determining that the three-dimensional cross section of the study region is not dispersed, wherein the threshold value of the three-dimensional cross section dispersion coefficient is required.
In one embodiment, the three-dimensional section dispersion coefficient threshold is determined according to the oil reservoir anatomy enclosed by the drilled blocks, that is, three-dimensional section dispersion coefficients of different depth points of the plurality of drilled block enclosed sections are respectively calculated to obtain a relation chart of the three-dimensional section dispersion coefficients and the depths, and the three-dimensional section dispersion coefficient corresponding to the two communicated sections of the section is the three-dimensional section dispersion coefficient threshold. The method for judging the fault with two communicated fault disks comprises the following steps: if the properties of the two disks of stratum fluids of the fault, such as the properties of stratum water, stratum crude oil and the like, tend to be consistent, the two disks of stratum of the fault can be communicated very possibly; the pressure of the two disks of stratum of the fault can be judged, if the pressures are the same or tend to be the same, the two disks of stratum of the fault are communicated, and the like. The fault trap here refers to the trap formed under fault control. Correspondingly, the trap of the drilled fault block is the trap drilled, and the communication dredging performance of the corresponding fault can be determined according to the drilling condition.
In the embodiment of the present invention, based on the drilling data, i.e. the data of the drilled block trap, it can be found that: in the drilled broken block trap, the region with the three-dimensional section dredging coefficient larger than or equal to 5.8/Mpa.m has good dredging property, and the region with the three-dimensional section dredging coefficient smaller than 5.8/Mpa.m has poor dredging property; and further determining 5.8/Mpa.m as a three-dimensional section dispersion coefficient threshold value for determining the connectivity dispersion of grid points of other faults. For example, for other grid points of the fault, if the three-dimensional section dispersion coefficient of the grid point is greater than or equal to 5.8/Mpa.m, the grid point is determined to have good dispersion, and the oil and gas migration requirement is met; and if the three-dimensional section dredging coefficient of the grid point is less than 5.8/Mpa.m, determining that the grid point has poor dredging and does not meet the dredging oil-gas migration requirement.
In an embodiment, the method further comprises: and determining to drill the fault block trap of the research area during three-dimensional fault dredging of the research area.
The method provided by the embodiment of the invention can also predict the migration path and the trajectory of the oil gas along a series of forward fault blocks or reverse fault blocks, and analyze the oil gas accumulation condition; and whether a water injection layer or an oil layer controlled by the fault is communicated can be judged, so that a scientific and reasonable working system is formulated, and the drilling success rate and the development economic benefit of the fault block trap are improved.
Based on the above embodiments, the present invention provides the following embodiments to explain a detailed flow of the quantitative determination method of three-dimensional fault canalization, and fig. 3 is a detailed flow chart of the quantitative determination method of three-dimensional fault canalization in the embodiments of the present invention, as shown in fig. 3:
301, acquiring section data and layer data of a research area according to the three-dimensional seismic data after the research area is overlapped;
303, analyzing the relation between upper and lower adjacent levels in the level structure surface model in a three-dimensional space, and eliminating level distortion points causing string levels or crossing to obtain a new level structure surface model;
308, acquiring data of the above-ground layered system according to the logging information;
313, calculating the actual mudstone smearing displacement on the cross section of each grid point according to the inclination angle and the fault line distance of each grid point;
315, obtaining the thickness of a mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum;
and 319, determining three-dimensional fault dispersion of the research area when the three-dimensional section dispersion coefficient is larger than a three-dimensional section dispersion coefficient threshold value, and otherwise determining that the three-dimensional fault of the research area is not dispersed.
Of course, it is understood that other variations of the above detailed flow can be made, and all such variations are intended to fall within the scope of the present invention.
An embodiment is given below to illustrate a specific application of the quantitative determination method of three-dimensional fault canalization.
S11: and loading the target region post-stack seismic data into interpretation software Landmark to obtain fault data and horizon data.
S12: loading fault data and layer data into professional modeling software petrel, respectively constructing a layer model and a fault model to obtain a three-dimensional geological model, correcting the layer model and the fault model based on logging information, processing a layer and section cross-over relation according to the corrected layer model and the corrected section model to form the three-dimensional geological model containing the layer and the section, and obtaining a schematic diagram of the three-dimensional geological model in the embodiment of the invention shown in FIG. 4.
S13: and carrying out gridding processing on the section in the three-dimensional geological model to obtain a grid model, wherein the size of a grid specifically used for gridding is defined according to research needs, the grid step size of 25 x 25m is adopted in the embodiment, and then the dip angle and the fault distance of each grid point are obtained. Specifically, referring to fig. 2, P, Q in fig. 2 is two arbitrary points on the cross section, and it can be seen from fig. 2 that the cross section inclination angles of the two points are obviously different.
S14: the method comprises the steps of obtaining the thickness of a mudstone layer in each grid point in a section of a grid model and displacement and depth data of actual mudstone smearing on the section, and calculating the distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section, wherein the thickness of the mudstone layer in each grid point is determined according to formation lithology data of a research area, and fig. 5 is a schematic diagram of a lithology curve chart in the embodiment of the invention and is obtained by loading a las-format logging curve into professional logging interpretation software Geolology.
S15: and calculating the dredging coefficient of the three-dimensional section according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section.
S16, when the three-dimensional section dispersion coefficient is larger than a three-dimensional section dispersion coefficient threshold value, determining three-dimensional section dispersion of the research area, otherwise determining that the three-dimensional section of the research area is not dispersed, wherein the three-dimensional section dispersion coefficient threshold value is determined according to two drilled broken block traps, and according to well drilling data, key accumulation periods of the two drilled broken block traps are chalk systems, are dry wells and display good oil and gas, and the fact that the oil source of the area is sufficient is indicated. FIG. 6 is a chart of the relationship between the three-dimensional fracture surface dispersion coefficient and the depth in the embodiment of the present invention, wherein the length 20, the length 19 and the length 2 are three drilling wells, and the three-dimensional fracture surface dispersion coefficient of the oil-containing controlled ring fracture in the high position is found to be above 5.85mp.s by the chart analysis; and the three-dimensional section dispersion coefficient of the oil-containing ring control fault at the high part of the failure target layer is below 5.85 mp.s. Namely, the three-dimensional section dispersion coefficient threshold value of the oil-containing control ring fault at the high part is determined to be 5.85 mp.s. Since the three-dimensional fracture conductivity threshold is derived from the drilled reservoir, well drilling verification is obtained, and therefore, the three-dimensional fracture conductivity threshold can represent geological features of the target area.
S17, dividing a target area three-dimensional section with a dispersion coefficient C larger than 15mp.s into an I-type fault with excellent dispersion, dividing a target area three-dimensional section with a dispersion coefficient C larger than 10mp.s and smaller than or equal to 15mp.s into a II-type fault with good dispersion, dividing a target area three-dimensional section with a dispersion coefficient C smaller than 10mp.s and larger than 5.8mp.s into a III-type fault with general dispersion, and dividing a target area three-dimensional section with a dispersion coefficient C smaller than 5.8mpa.s into a non-dispersion closed IV-type fault, wherein the I-type fault controls high-position trap formed by dispersion, oil and gas easily moves upwards across the lateral migration of the fault to form accumulation and trap for preferred arrangement; class II fault control trap; the trap of the type III fault control is a trap with higher risk; the trap controlled by the IV fault is a non-dredging fault, oil and gas are not easy to form accumulation across the fault, the trap is not formed at the high part of the fault, and drilling is not recommended. See the guiding quantitative evaluation standard of table 1 in detail, and deploy the well position according to the above-mentioned thought, thereby avoiding the risk and providing reliable guidance for exploration deployment and well drilling.
TABLE 1
In summary, in the method provided by the embodiment of the present invention, the section data and the horizon data of the research area are obtained according to the post-stack three-dimensional seismic data of the research area; establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area; performing gridding treatment on the section in the three-dimensional geological model to obtain a grid model; obtaining the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section; calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section; and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed. In the process, the three-dimensional seismic data and the logging information of the study area after the superposition are comprehensively considered, the three-dimensional geological model is finally established, after the grid model is obtained, the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement along the section are quantitatively obtained, and then the three-dimensional section dredging coefficient is quantitatively calculated, so that the process of judging whether the three-dimensional fault in the study area is dredged or not according to the three-dimensional section dredging coefficient is more accurate.
The embodiment of the invention also provides a quantitative determination device of three-dimensional fault canalization, the principle of which is similar to that of the quantitative determination method of three-dimensional fault canalization, and the description is omitted here.
Fig. 7 is a schematic diagram of a quantitative determination apparatus for three-dimensional fault canalization in an embodiment of the invention, as shown in fig. 7, the apparatus includes:
a data obtaining module 701, configured to obtain section data and horizon data of a research area according to the post-stack three-dimensional seismic data of the research area;
a three-dimensional geological model building module 702, configured to build a three-dimensional geological model according to the section data, the horizon data, and the logging information of the research area;
a grid model obtaining module 703, configured to perform meshing processing on a section in the three-dimensional geological model to obtain a grid model;
the first calculation module 704 is used for acquiring the thickness of the mudstone layer in each grid point in the section of the grid model, the actual mudstone smearing displacement on the section and the depth data, and calculating the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
the second calculation module 705 is used for calculating a three-dimensional fracture surface dredging coefficient according to the mudstone distribution thickness and the fracture surface pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface;
a grooming determination module 706, configured to determine a three-dimensional fault grooming in the study region when the three-dimensional section grooming coefficient is greater than a three-dimensional section grooming coefficient threshold, or determine that the three-dimensional fault in the study region is not groomed.
In one embodiment, the logging information includes at least one of shale content data, gamma data, sonic data, and resistivity data.
In one embodiment, the three-dimensional geological model building module 702 comprises:
a horizon model establishing module 7021 configured to establish a horizon model according to the horizon data;
a section model establishing module 7022, configured to establish a section model according to the section data;
a correction module 7023 configured to correct the horizon model and the fault model based on the logging information;
and a generating module 7024, configured to process the intersection relationship between the horizon and the section according to the corrected horizon model and the corrected section model, and form a three-dimensional geological model including the horizon and the section.
In an embodiment, the horizon model building module 7021 is specifically configured to:
constructing a horizon structural surface model according to the horizon data;
analyzing the relation of upper and lower adjacent levels in the level structure surface model in a three-dimensional space, and eliminating level distortion points causing series or cross to obtain a new level structure surface model;
and smoothing the new horizon structural surface model to obtain a horizon model.
In an embodiment, the section model building module 7022 is specifically configured to:
removing malformed data points in the section data to obtain ridge breaking data, wherein the ridge breaking data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault ridge data;
and analyzing the cross-over relation of the fault plane in the fault plane model, and correcting the part which does not meet the preset requirement in the fault plane model to obtain the fault model.
In an embodiment, the correction module 7023 is specifically configured to:
acquiring data of an aboveground layered system according to the logging information;
correcting the horizon model by using the data of the aboveground layered system to obtain a corrected horizon model;
and correcting the fault model by using the corrected horizon model.
In an embodiment, the apparatus further comprises a third calculation module 707 for:
and calculating the actual mudstone smearing displacement on the fracture surface in each grid point according to the dip angle and the fault distance in each grid point.
In an embodiment, the apparatus further comprises a mudstone thickness obtaining module 708 for:
acquiring formation lithology data of the research area according to the logging information of the research area;
and obtaining the thickness of the mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum.
In an embodiment, the first calculating module 704 is specifically configured to:
the method comprises the following steps of calculating the mudstone distribution thickness of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface according to the thickness of the mudstone layer in each grid point in the fracture surface of the grid model and the actual mudstone smearing displacement on the fracture surface by adopting the following formula:
Li＝Hi/Si
wherein L isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; hiThe thickness of the mudstone layer in the ith grid point is shown; siThe displacement of actual mudstone smearing on the section;
calculating the section pressure at each grid point from the depth data at each grid point using the following formula:
Pi＝10-3Mi(ρl-ρw)·g·cosa
wherein, PiThe section pressure in the ith grid point is taken as the pressure; miDepth data in the ith grid point; rholIs the average density of the overburden; rhowIs the average density of formation water; g is the acceleration of gravity; a is the tilt angle in the ith grid point.
In an embodiment, the second calculating module 705 is specifically configured to:
calculating the dredging coefficient of the three-dimensional section according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section by adopting the following formula:
wherein C is a three-dimensional section dredging coefficient; l isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; piThe section pressure in the ith grid point.
In summary, in the apparatus provided in the embodiment of the present invention, the section data and the horizon data of the research area are obtained according to the post-stack three-dimensional seismic data of the research area; establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area; performing gridding treatment on the section in the three-dimensional geological model to obtain a grid model; obtaining the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section; calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section; and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed. In the process, the three-dimensional seismic data and the logging information of the study area after the superposition are comprehensively considered, the three-dimensional geological model is finally established, after the grid model is obtained, the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement along the section are quantitatively obtained, and then the three-dimensional section dredging coefficient is quantitatively calculated, so that the process of judging whether the three-dimensional fault in the study area is dredged or not according to the three-dimensional section dredging coefficient is more accurate.
An embodiment of the present application further provides a computer device, fig. 8 is a schematic diagram of the computer device in the embodiment of the present invention, the computer device is capable of implementing all steps in the quantitative determination method of three-dimensional fault canalization in the foregoing embodiment, and the computer device specifically includes the following contents:
a processor (processor)801, a memory (memory)802, a communication Interface (Communications Interface)803, and a communication bus 804;
the processor 801, the memory 802 and the communication interface 803 complete mutual communication through the communication bus 804; the communication interface 803 is used for realizing information transmission among related devices such as server-side devices, detection devices, client-side devices and the like;
the processor 801 is configured to call a computer program in the memory 802, and the processor implements all the steps of the quantitative determination method of three-dimensional fault sparsity in the above embodiments when executing the computer program.
Embodiments of the present application also provide a computer-readable storage medium, which can implement all the steps of the quantitative determination method of three-dimensional fault sparsity in the above embodiments, and the computer-readable storage medium stores thereon a computer program, which, when executed by a processor, implements all the steps of the quantitative determination method of three-dimensional fault sparsity in the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (22)
1. A method for quantitative determination of three-dimensional fault canalization, comprising:
acquiring section data and horizon data of a research area according to the post-stack three-dimensional seismic data of the research area;
establishing a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area;
performing gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
obtaining the thickness of a mudstone layer in each grid point in the section of the grid model, and displacement and depth data of actual mudstone smearing on the section, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
calculating a three-dimensional section dredging coefficient according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section;
and when the three-dimensional section dispersion coefficient is larger than the three-dimensional section dispersion coefficient threshold value, determining the three-dimensional section dispersion of the research area, otherwise, determining that the three-dimensional section of the research area is not dispersed.
2. The method of quantitative determination of three-dimensional fault conductance according to claim 1, wherein the well log information includes at least one of shale content data, gamma data, sonic data, and resistivity data.
3. The method of claim 1, wherein building a three-dimensional geological model from the profile data, horizon data, and well log information comprises:
establishing a horizon model according to the horizon data;
establishing a fault model according to the section data;
correcting the horizon model and the fault model based on the logging information;
and processing the connection relation between the horizon and the section according to the corrected horizon model and the corrected section model to form a three-dimensional geological model containing the horizon and the section.
4. The method of quantitative determination of three-dimensional fault canalization of claim 3, wherein building a horizon model from the horizon data comprises:
constructing a horizon structural surface model according to the horizon data;
analyzing the relation of upper and lower adjacent levels in the level structure surface model in a three-dimensional space, and eliminating level distortion points causing series or cross to obtain a new level structure surface model;
and smoothing the new horizon structural surface model to obtain a horizon model.
5. The method of claim 3, wherein establishing a fault model based on the cross-sectional data comprises:
removing malformed data points in the section data to obtain ridge breaking data, wherein the ridge breaking data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault ridge data;
and analyzing the cross-over relation of the fault plane in the fault plane model, and correcting the part which does not meet the preset requirement in the fault plane model to obtain the fault model.
6. The method of quantitative determination of three-dimensional fault conductance according to claim 3, wherein correcting the horizon model and the fault model based on the well log information comprises:
acquiring data of an aboveground layered system according to the logging information;
correcting the horizon model by using the data of the aboveground layered system to obtain a corrected horizon model;
and correcting the fault model by using the corrected horizon model.
7. The method of quantitative determination of three-dimensional fault canalization of claim 1, further comprising:
and calculating the actual mudstone smearing displacement on the fracture surface in each grid point according to the dip angle and the fault distance in each grid point.
8. The method of quantitative determination of three-dimensional fault canalization of claim 1, further comprising:
acquiring formation lithology data of the research area according to the logging information of the research area;
and obtaining the thickness of the mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum.
9. The method of claim 1, wherein the steps of obtaining the mudstone thickness at each grid point in the fracture surface of the grid model, the displacement of actual mudstone smearing on the fracture surface and the depth data, and calculating the mudstone distribution thickness and the fracture surface pressure of the mudstone at each grid point along the actual smearing displacement of the fracture surface comprise:
the method comprises the following steps of calculating the mudstone distribution thickness of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface according to the thickness of the mudstone layer in each grid point in the fracture surface of the grid model and the actual mudstone smearing displacement on the fracture surface by adopting the following formula:
Li＝Hi/Si
wherein L isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; hiThe thickness of the mudstone layer in the ith grid point is shown; siThe displacement of actual mudstone smearing on the section;
calculating the section pressure at each grid point from the depth data at each grid point using the following formula:
Pi＝10-3Mi(ρl-ρw)·g·cosa
wherein, PiThe section pressure in the ith grid point is taken as the pressure; miDepth data in the ith grid point; rholIs the average density of the overburden; rhowIs the average density of formation water; g is the acceleration of gravity; a is the tilt angle in the ith grid point.
10. The quantitative determination method of three-dimensional fault dredging as claimed in claim 1, characterized in that the three-dimensional fault dredging coefficient is calculated according to the mudstone distribution thickness and the fracture pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture by using the following formula:
wherein C is a three-dimensional section dredging coefficient; l isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; piThe section pressure in the ith grid point.
11. A quantitative determination apparatus of three-dimensional fault canalization, comprising:
the data acquisition module is used for acquiring section data and layer data of the research area according to the post-stack three-dimensional seismic data of the research area;
the three-dimensional geological model establishing module is used for establishing a three-dimensional geological model according to the section data, the layer data and the logging information of the research area;
the grid model obtaining module is used for carrying out gridding processing on the section in the three-dimensional geological model to obtain a grid model;
the first calculation module is used for acquiring the thickness of the mudstone layer in each grid point in the section of the grid model, the actual mudstone smearing displacement on the section and depth data, and calculating the mudstone distribution thickness and section pressure of the mudstone layer in each grid point along the actual smearing displacement of the section;
the second calculation module is used for calculating a three-dimensional fracture surface dredging coefficient according to the mudstone distribution thickness and the fracture surface pressure of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface;
and the dispersion determination module is used for determining the dispersion of the three-dimensional fault in the research area when the dispersion coefficient of the three-dimensional section is larger than the threshold value of the dispersion coefficient of the three-dimensional section, and otherwise determining that the three-dimensional fault in the research area is not dispersed.
12. The quantitative determination of three-dimensional fault conductance according to claim 11, wherein the well log information includes at least one of shale content data, gamma data, sonic data, and resistivity data.
13. The apparatus for quantitative determination of three-dimensional fault conductance of claim 11, wherein the three-dimensional geological model building module comprises:
the horizon model establishing module is used for establishing a horizon model according to the horizon data;
the section model establishing module is used for establishing a section model according to the section data;
the correction module is used for correcting the horizon model and the fault model based on the logging information;
and the generation module is used for processing the connection relation between the horizon and the section according to the corrected horizon model and the corrected section model to form a three-dimensional geological model containing the horizon and the section.
14. The apparatus of claim 13, wherein the horizon model building module is specifically configured to:
constructing a horizon structural surface model according to the horizon data;
analyzing the relation of upper and lower adjacent levels in the level structure surface model in a three-dimensional space, and eliminating level distortion points causing series or cross to obtain a new level structure surface model;
and smoothing the new horizon structural surface model to obtain a horizon model.
15. The apparatus of claim 13, wherein the section model building module is configured to:
removing malformed data points in the section data to obtain ridge breaking data, wherein the ridge breaking data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault ridge data;
and analyzing the cross-over relation of the fault plane in the fault plane model, and correcting the part which does not meet the preset requirement in the fault plane model to obtain the fault model.
16. The quantitative determination of three-dimensional fault canalization apparatus of claim 13, wherein the correction module is specifically configured to:
acquiring data of an aboveground layered system according to the logging information;
correcting the horizon model by using the data of the aboveground layered system to obtain a corrected horizon model;
and correcting the fault model by using the corrected horizon model.
17. The quantitative determination of three-dimensional fault canalization apparatus of claim 11, further comprising a third calculation module for:
and calculating the actual mudstone smearing displacement on the fracture surface in each grid point according to the dip angle and the fault distance in each grid point.
18. The quantitative determination of three-dimensional fault canalization apparatus of claim 11, further comprising a mudstone thickness acquisition module for:
acquiring formation lithology data of the research area according to the logging information of the research area;
and obtaining the thickness of the mudstone layer in each grid point in the section of the grid model according to the lithological data of the stratum.
19. The quantitative determination of three-dimensional fault canalization apparatus of claim 11, wherein the first calculation module is specifically configured to:
the method comprises the following steps of calculating the mudstone distribution thickness of the mudstone layer in each grid point along the actual smearing displacement of the fracture surface according to the thickness of the mudstone layer in each grid point in the fracture surface of the grid model and the actual mudstone smearing displacement on the fracture surface by adopting the following formula:
Li＝Hi/Si
wherein L isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; hiThe thickness of the mudstone layer in the ith grid point is shown; siThe displacement of actual mudstone smearing on the section;
calculating the section pressure at each grid point from the depth data at each grid point using the following formula:
Pi＝10-3Mi(ρl-ρw)·g·cosa
wherein, PiThe section pressure in the ith grid point is taken as the pressure; miDepth data in the ith grid point; rholIs the average density of the overburden; rhowIs the average density of formation water; g is the acceleration of gravity; a is the tilt angle in the ith grid point.
20. The quantitative determination of three-dimensional fault canalization apparatus of claim 11, wherein the second calculation module is specifically configured to:
calculating the dredging coefficient of the three-dimensional section according to the mudstone distribution thickness and the section pressure of the mudstone layer in each grid point on the actual smearing displacement of the section by adopting the following formula:
wherein C is a three-dimensional section dredging coefficient; l isiThe mudstone distribution thickness of the mudstone layer in the ith grid point on the actual smearing displacement of the fracture surface is determined; piThe section pressure in the ith grid point.
21. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 10 when executing the computer program.
22. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 10.
Priority Applications (1)
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