CN114114411B - Quantitative determination method and device for three-dimensional fault dredge - Google Patents
Quantitative determination method and device for three-dimensional fault dredge Download PDFInfo
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- G—PHYSICS
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/301—Analysis for determining seismic cross-sections or geostructures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/282—Application of seismic models, synthetic seismograms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6169—Data from specific type of measurement using well-logging
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- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/64—Geostructures, e.g. in 3D data cubes
- G01V2210/642—Faults
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/66—Subsurface modeling
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Abstract
The invention provides a quantitative determination method and a quantitative determination device for three-dimensional fault dredge, 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; gridding the section in the three-dimensional geological model to obtain a grid model; acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in the grid points along the actual mudstone daubing displacement of the cross section; according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient; and when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged. The invention can quantitatively analyze the three-dimensional fault dredge and has high accuracy.
Description
Technical Field
The invention relates to the technical field of oil and gas exploration and development, in particular to a quantitative determination method and device for three-dimensional fault dredge.
Background
In the exploration and development practice of a fault block oil-gas reservoir, a fault can play a role in sealing oil gas and dredging the oil gas, and the fault without sealing can enable the oil gas to pass through and laterally migrate into the reservoir after forming the oil gas.
Fault sealing research is the opposite face and key point of fault dredging research, and fault sealing research is always a difficult problem for hydrocarbon geologists. The fault seal has bi-directionality, namely vertical seal and lateral seal. The fault sealing performance is evaluated, namely, on the basis of well known fault characteristics of a research area, a plurality of variables with larger influence on the fault sealing or opening of the area are screened, the correct fault sealing mechanism is tightly combined, various accurate geology and geophysical prospecting data are utilized, and a proper evaluation method is selected for calculation and analysis, so that the evaluation effect reflects the objective reality of the fault sealing of the area to the greatest extent. Many scholars consider fault closure to be based on (1) lithology of reservoirs versus non-reservoirs; (2) physical properties of the filler in the fracture zone. Early fault closure mechanism studies hypothesized that smearing of clay-rich layers along the fault plane could produce hypotonic fault mud in both reservoirs. Recent studies have shown that similar clay smears or fault mud are ubiquitous in the near shore deepwater zone at the fault level of shielding the hydrocarbon accumulation. In recent years, clay smearing, especially fault mud ratio (SGR), is used for evaluating and predicting fault sealing performance of thick-layer clastic stratum sequence areas, and many students at home and abroad do much work and have made great progress; after this, most foreign students are devoted to study the characteristics of faults themselves, and rarely quantitatively evaluate fault closure methods.
In summary, considering the existing fault dredging determination method, the blocking property of the fault is usually analyzed first, the blocked fault cannot dredge oil gas, the non-blocked fault can dredge oil gas, an oil gas seepage channel is formed, so that the oil gas is transferred to the fault pair tray across the fault, and in the fault analysis process, two problems exist. Firstly, it is: in most of the existing methods for determining the closure, the closure is determined by an SGR fault mud ratio method. When the SGR method is implemented, only the mudstone thickness and the breaking distance of a fault disc are often involved, and factors such as lithology influence, section compaction and closing degree, actual mudstone smearing displacement change and the like of the two fault discs are not considered, so that the accuracy of determining the closure is not high. Secondly, to evaluate fault dredging capability, firstly, the closure is analyzed, the process is complex, and no direct quantitative parameters and calculation method for evaluating fault dredging capability exist, so that the evaluation efficiency is low. The calculation result is easy to deviate and mislead, so that the analysis of the closure of the broken block trap is incomplete, and exploration disfavored is caused.
Therefore, a quantitative determination method of fault diversion is lacking at present.
Disclosure of Invention
The embodiment of the invention provides a quantitative determination method of three-dimensional fault dredge, which is used for quantitatively analyzing the three-dimensional fault dredge, and has high accuracy, and the method comprises the following steps:
Acquiring section data and horizon data of the research area according to the three-dimensional seismic data after the research area is overlapped;
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;
acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the cross section;
according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient;
and when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged.
The embodiment of the invention provides a quantitative determination device for three-dimensional fault dredge, which is used for quantitatively analyzing the three-dimensional fault dredge, and has high accuracy, and the device comprises:
the data acquisition module is used for acquiring section data and horizon data of the research area according to the three-dimensional seismic data after the research area is overlapped;
The three-dimensional geological model building module is used for building a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area;
the grid model obtaining module is used for carrying out gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
the first calculation module is used for obtaining the thickness of the shale layer in each grid point in the section of the grid model, the actual mudstone daubing displacement and depth data on the section, and calculating the distribution thickness of the mudstone and the section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the section;
the second calculation module is used for calculating a three-dimensional section dredging coefficient according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section;
and the dredging property determining module is used for determining that the three-dimensional fault of the research area is dredged when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, or determining that the three-dimensional fault of the research area is not dredged.
The embodiment of the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the quantitative determination method of the three-dimensional fault guiding property is realized when the processor executes the computer program.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program for executing the quantitative determination method of three-dimensional fault breakout.
In the embodiment of the invention, section data and horizon data of a research area are obtained according to the three-dimensional seismic data after the research area is overlapped; 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; acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the cross section; according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient; and when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged. In the process, three-dimensional seismic data and logging information after the study area is overlapped are comprehensively considered, a three-dimensional geological model is finally established, after the grid model is obtained, the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point 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 of the study area is dredged according to the three-dimensional section dredging coefficient is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow chart of a method for quantitatively determining three-dimensional fault grooming in an embodiment of the invention;
FIG. 2 is a schematic illustration of the displacement of an actual mudstone smear on a section in an embodiment of the invention;
FIG. 3 is a detailed flow chart of a method for quantitatively determining three-dimensional fault diversion in an embodiment of the present invention;
FIG. 4 is a schematic representation of a three-dimensional geologic model in accordance with an embodiment of the invention;
FIG. 5 is a schematic illustration of a lithology graph plate in an embodiment of the invention;
FIG. 6 is a graph of the relationship between the three-dimensional profile grooming coefficients and depth in an embodiment of the invention;
FIG. 7 is a schematic diagram of a quantitative determination device for three-dimensional fault diversion in an embodiment of the invention;
fig. 8 is a schematic diagram of a computer device in an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present application and their descriptions herein are for the purpose of explaining the present application, but are not to be construed as limiting the application.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are open-ended terms, meaning including, but not limited to. The description of the reference 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, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The order of steps involved in the embodiments is illustrative of the practice of the application, and is not limited and may be suitably modified as desired.
Fig. 1 is a flowchart of a method for quantitatively determining three-dimensional fault dredge in an embodiment of the present invention, as shown in fig. 1, the method includes:
step 101, acquiring section data and horizon data of a research area according to three-dimensional seismic data of the research area after being stacked;
102, establishing a three-dimensional geological model according to the section data, the horizon data and logging information of a research area;
step 103, carrying out gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
104, acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual displacement and depth data of the shale smearing on the cross section, and calculating the distribution thickness of the shale layer in each grid point along the actual displacement of the shale smearing on the cross section and the pressure of the cross section;
105, calculating a three-dimensional section dredging coefficient according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section;
and step 106, determining that the three-dimensional fault of the research area is dredged when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, otherwise, determining that the three-dimensional fault of the research area is not dredged.
In the method provided by the embodiment of the invention, the three-dimensional seismic data and logging information of the research area after being overlapped are comprehensively considered, a three-dimensional geological model is finally established, after the grid model is obtained, the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point 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 of the research area is dredged according to the three-dimensional section dredging coefficient is more accurate.
In the specific implementation, in step 101, section data and horizon data of a research area are obtained according to three-dimensional seismic data after the research area is stacked, specifically including loading the three-dimensional seismic data after the research area is stacked into professional seismic interpretation software Landmark or Geoeast, releasing the section and a target stratum, obtaining total breaking distance, inclination angle, trend and other factors of the section, and obtaining layer thickness, inclination angle and other factors of the stratum. When the section data and horizon data are obtained by the existing method and then fault sealing is determined to analyze the dredge, drilling data are mostly used, 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 for analysis and processing, the prior method can only perform simple two-dimension data calculation analysis and cannot perform three-dimension analysis. In contrast, the analytical processing range is limited and does not meet practical drilling requirements well. The three-dimensional seismic data used in the embodiment of the invention meets the requirement of three-dimensional analysis.
In step 102, a three-dimensional geologic model is created from the section data, horizon data, and logging information for the investigation region, and in one embodiment, the three-dimensional geologic model is created from the section data, horizon data, and logging information, including:
Establishing a horizon model according to 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 intersection relation of 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 horizons and the sections.
In the specific implementation, in order to build a structural layer model of each objective layer according to the explained layer data, in the specific implementation, a structural model of a key surface is built in the structural layer modeling (the key surface is relatively more data information, and the layer of the structural surface, such as an oil group of a research area, can be accurately built).
In one embodiment, building a horizon model from horizon data includes:
s1: constructing a horizon construction surface model according to horizon data;
loading the prepared horizon data into professional modeling software such as petrol or GPTmodel, and constructing a horizon construction surface model according to the methods of Keli Jin Chazhi, least squares and the like; the stratum erosion and other geological conditions can be processed according to the contact relation of the layers; the method can use seismic interpretation or result data of other software as constraint conditions, can generate a stratum model firstly, and simultaneously build a small-layer construction layer model under the constraint of a key layer; and then vertically subdividing the grids according to the requirements of each small layer.
S2: and analyzing the relation between upper and lower adjacent layers in the layer structure surface model in a three-dimensional space, and eliminating the layer malformation points causing the serial layers or the intersection to obtain a new layer structure surface model.
S3: and carrying out smoothing treatment on the new horizon construction 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 the fault model construction is to carry out visual expression on the topological relation, geometric characteristics and attribute characteristics among the faults, and take the faults as the boundaries of stratum units to construct a fault model; the fault data model can be realized by constructing a fault model by using a section method by using section data, constructing fault planes based on contour line reconstruction, constructing fault planes with small inclination and inclination angles of oil fault planes, constructing fault models by using a plurality of fault planes, and performing space on the model in a county of the space, space calculation, space analysis and the like. The specific implementation can be carried out according to the following steps:
in one embodiment, building a fault model from the section data includes:
s1: removing abnormal data points in the section data to obtain edge cutting data, wherein the edge cutting data comprises fault line data and fault point composition data;
The interpreted fault data are loaded into professional modeling software such as petrol or GPTmodel, the fault data are analyzed under a three-dimensional window, a range needing modeling is selected, abnormal data points are removed, and the specific data formats are Irap, zmap, CPS-3.
S2: generating a fault plane model according to the fault edge data;
specifically, a method such as Keli Jin Chazhi can be adopted to generate a fault plane model.
S3: and analyzing the connection relation of the fault surface model interruption layers, and correcting the part of the fault surface model which does not meet the preset requirements to obtain the fault model, wherein the preset requirements comprise geological rules and characteristics, and correcting the fault model in an editing mode.
In an embodiment, correcting the horizon model and the fault model based on the logging information includes:
s1: acquiring uphole layered system data according to logging information;
and establishing an uphole layering system according to the regional geological knowledge and logging information to obtain uphole layering system data, wherein the layering system name and the seismic upper horizon name are consistent.
S2: correcting the horizon model by using the data of the layering system on the well to obtain a corrected horizon model, so that the horizon model and the layering system on the well tend to be consistent, and the distribution of the morphology of the horizon structure is more consistent with the real geological condition.
S3: and correcting the fault model by using the corrected horizon model, and synchronously editing 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, a gridding process is performed on the section in the three-dimensional geological model to obtain a grid model, and the grid size can be set according to the requirement of research precision, and the gridding section model can be specifically:
s1: and preliminarily selecting a cross section range needing gridding according to the research requirements and the cross section-layer interface relation.
S2: the type of mesh, such as a triangular mesh or a rectangular mesh, is selected based on the cross-sectional geometry.
S3: and gridding the spatial section spread of the target fault, wherein parameters such as gridding step length, grid size and the like can be set according to actual research requirements, such as 4m multiplied by 4m.
In particular, in order to improve the quality of the grid, the main direction of the grid selects the trend direction of the cross section in the grid formation process, and the local area of the cross section can be encrypted for precision requirement.
In an embodiment, the method further comprises:
and calculating the displacement of the actual mudstone smearing on the section in each grid point according to the inclination angle and the breaking distance in each grid point.
Fig. 2 is a schematic diagram of displacement of actual mudstone smearing on a section in an embodiment of the present invention, where the following formula may be used to calculate the displacement of actual mudstone smearing on a section in each grid point according to the inclination angle and the break distance in each grid point:
S i ＝D i /sina
wherein S is i The displacement of the actual mudstone smearing on the section in the ith grid point; d (D) i The unit is cm for the break distance in the ith grid point; a is the dip in the ith grid point.
In an embodiment, the method further comprises:
obtaining stratum lithology data of the research area according to logging information of the research area;
and obtaining the thickness of the shale layer in each grid point in the section of the grid model according to the stratum lithology data.
In an embodiment, the logging information includes at least one of shale content data, gamma data, acoustic data, and resistivity data.
In the above embodiment, the formation lithology data includes formation lithology, and the logging information of the investigation region may be calibrated to the formation lithology of the investigation region, specifically including loading the las format log into professional logging interpretation software Geolog or other software, where the las format log includes a clay content curve, a gamma curve, an acoustic curve, and a resistivity curve.
In one embodiment, the formation lithology of the investigation region may be calibrated according to the argillaceous content curve and the gamma curve, and specifically includes: determining a argillaceous content differential value and a gamma differential value of the argillaceous according to response characteristics of the argillaceous in the research area, wherein the argillaceous content data in the research area, which is larger than the argillaceous content differential value, in the curve, and the part, which is larger than the gamma differential value, in the gamma curve, represents that the argillaceous content is high, and the part is marked as the argillaceous; otherwise, the stratum is marked as sandstone, so that lithology information of the stratum of the whole research area is obtained.
In other embodiments, lithology information may also be obtained by lithology calibration using other curves. For example, the gamma curve and the resistivity curve are used for calibration, and according to the response characteristics of the sand shale in the research area, the part of the gamma curve in which the gamma data is smaller than the gamma-region value and the resistivity data in the resistivity curve in which the resistivity data is larger than the resistivity region is calibrated as sandstone, otherwise, the part of the gamma curve in which the gamma data is larger than the resistivity region is calibrated as mudstone, so that lithology information of the stratum in the whole research area is obtained.
And obtaining the thickness of the shale layer in each grid point in the section of the grid model according to the stratum lithology data, particularly, when the stratum lithology data in the grid points are loaded, if the thickness of the shale layer is larger than the size of the grid, the whole grid points are the shale, the thickness of the shale layer is the longitudinal breaking distance size, and if the thickness of the shale layer is smaller than the longitudinal breaking distance size, the calculation is participated according to the thickness of the actual shale layer.
The depth data in each grid point can be directly read from the section data with depth according to the spatial fault spread of the target fault after gridding.
In an embodiment, obtaining the thickness of the shale layer in each grid point in the section of the grid model, the displacement and depth data of the actual mudstone smearing on the section, and calculating the thickness of the mudstone distribution and the section pressure of the shale layer in each grid point along the actual mudstone smearing displacement of the section, wherein the method comprises the following steps:
the following formula is adopted, and according to the thickness of the shale layer in each grid point in the section of the grid model and the actual displacement of the shale smearing on the section, the distribution thickness of the shale layer in each grid point along the actual displacement of the shale smearing on the section is calculated:
L i ＝H i /S i
wherein L is i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; h i Is the mud layer thickness in the ith grid point; s is S i The displacement of the actual mudstone smearing on the section;
the section pressure in each grid point is calculated from the depth data in each grid point using the following formula:
P i ＝10 -3 M i (ρ l -ρ w )·g·cosa
wherein P is i Is the section pressure in the ith grid point; m is M i Depth data within the ith grid point; ρ l Average density for overburden; ρ w Is the average density of the formation water; g is gravity acceleration; a is the dip in the ith grid point.
In the above embodiment, since the hydrostatic pressure above the fault does not act on the fault, the pressure on the fault to promote healing is mainly the pressure generated by the gravity of the skeleton of the overlying strata rock, the average density of the overlying strata is obtained from the logging data near the fracture zone, and the average density of the strata water is obtained from the testing data.
In one embodiment, the following formula is adopted, and the three-dimensional section dredging coefficient is calculated according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point:
wherein C is a three-dimensional section dredging coefficient; l (L) i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; p (P) i Is the section pressure in the ith grid point.
The three-dimensional section dredging coefficient of the whole section is obtained, and the dredging coefficient of each grid point can be obtained, so that a dredging coefficient plate is formed, and the observation is convenient.
In step 106, when the three-dimensional section guiding coefficient is greater than the three-dimensional section guiding coefficient threshold, determining that the three-dimensional fault of the research area is guided, otherwise determining that the three-dimensional fault of the research area is not guided, wherein the three-dimensional section guiding coefficient threshold is needed.
In one embodiment, the three-dimensional section dredging coefficient threshold is determined according to the oil reservoir anatomy of the drilled block trap, namely, three-dimensional section dredging coefficients of different depth points of the multiple drilled block trap fracture surfaces are calculated respectively, a relation chart of the three-dimensional section dredging coefficients and depth is obtained, and the three-dimensional section dredging coefficients corresponding to the faults of two communicated faults are the three-dimensional section dredging coefficient threshold. The judging method of the fault of the two-disc communication of the fault comprises the following steps: if the properties of two strata fluid such as stratum water, stratum crude oil and the like tend to be consistent, the two strata are most likely to be communicated; the method can also judge through the formation pressure of two strata of the fault, if the pressure is wanted to be identical or tends to be identical, namely the formation of two strata of the fault is communicated, and the like, and the method is different. Here, the broken block trap refers to a trap formed under fault control. Correspondingly, the drilled block trap is that the trap is drilled, and the communication dredging performance of the corresponding fault can be determined according to the drilling condition.
In the embodiment of the invention, according to drilling data, namely the drilled block trap data, it can be found that: in the drilled block trap, the three-dimensional section dredging coefficient is good in dredging of the area with the thickness of 5.8/Mpa.m and poor in dredging of the area with the thickness of less than 5.8/Mpa.m; further, 5.8/mpa.m may be determined as a three-dimensional fracture surface drainage coefficient threshold value for determining connectivity of grid points of other faults. For example, for other grid points of the fault, if the three-dimensional section dredging coefficient of the grid point is greater than or equal to 5.8/mpa.m, determining that the grid point has good dredging property and meets the oil and gas migration requirement; if the three-dimensional section dredging coefficient of the grid point is smaller than 5.8/mpa.m, determining that the dredging property of the grid point is poor, and not reaching the dredging oil and gas migration requirement.
In an embodiment, the method further comprises: and when the three-dimensional fault of the research area is dredged, determining to drill the broken block trap of the research area.
The method provided by the embodiment of the invention can also predict the migration path and track of the oil gas along a series of forward broken blocks or reverse broken blocks, and analyze the oil gas reservoir condition; and whether the water injection layer or the 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 broken block trap are improved.
Based on the above embodiments, the present invention proposes the following embodiment to explain the detailed flow of the quantitative determination method of three-dimensional fault breakout, and fig. 3 is a detailed flow chart of the quantitative determination method of three-dimensional fault breakout in the embodiment of the present invention, as shown in fig. 3:
step 301, obtaining section data and horizon data of a research area according to three-dimensional seismic data of the research area after being stacked;
step 302, constructing a horizon construction surface model according to horizon data;
step 303, analyzing the relationship between upper and lower adjacent horizons in the horizon construction surface model in a three-dimensional space, and eliminating the horizon malformation points causing strings or intersections to obtain a new horizon construction surface model;
Step 304, performing smoothing treatment on the new horizon construction surface model to obtain a horizon model;
step 305, eliminating abnormal data points in the section data to obtain edge cutting data, wherein the edge cutting data comprises fault line data and fault point composition data;
step 306, generating a fault plane model according to the fault plane data;
step 307, analyzing the connection relation of the fault surface model interruption surface, and correcting the part of the fault surface model which does not meet the preset requirement to obtain a fault model;
step 308, obtaining uphole layered system data according to logging information;
step 309, correcting the horizon model by using the above-well layering system data to obtain a corrected horizon model;
step 310, correcting the fault model by using the corrected horizon model;
step 311, processing the intersection relation of the horizon and the section according to the corrected horizon model and the corrected section model to form a three-dimensional geological model comprising the horizon and the section;
step 312, gridding the section in the three-dimensional geological model to obtain a grid model;
step 313, calculating the displacement of the actual mudstone smearing on the section in each grid point according to the inclination angle and the breaking distance in each grid point;
Step 314, obtaining formation lithology data of the research area according to the logging information of the research area;
step 315, obtaining the thickness of the mud layer in each grid point in the section of the grid model according to stratum lithology data;
step 316, obtaining depth data in each grid point in the section of the grid model;
step 317, calculating mud rock distribution thickness and section pressure on actual smearing displacement of the mud rock layer in each grid point along the section;
step 318, calculating a three-dimensional section dredging coefficient according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section;
and 319, determining that the three-dimensional fault of the research area is dredged when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, otherwise, determining that the three-dimensional fault of the research area is not dredged.
Of course, it is to be understood that other variations of the above detailed procedures are also possible, and all related variations should fall within the protection scope of the present invention.
A specific example is given below to illustrate a specific application of the quantitative determination method of three-dimensional fault dredge.
S11: and loading the post-stack seismic data of the target area into interpretation software Landmark to obtain fault data and horizon data.
S12: loading fault data and horizon data into professional modeling software petrel, respectively constructing a horizon model and a fault model to obtain a three-dimensional geological model, correcting the horizon model and the fault model based on logging information, and processing the intersection relationship of the horizons and the sections according to the corrected horizon model and the corrected section model to form the three-dimensional geological model comprising the horizons and the sections, wherein fig. 4 is a schematic diagram of the three-dimensional geological model in the embodiment of the invention.
S13: and carrying out gridding treatment 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 customized according to research requirements, in this embodiment, the step size of the grid of 25 multiplied by 25m is adopted, and then the inclination angle and the breaking distance of each grid point are obtained. Referring specifically to fig. 2, P, Q in fig. 2 is any two points on the cross section, and it is apparent from fig. 2 that the inclination angles of the cross section at the two points are different.
S14: acquiring the thickness of the shale layer in each grid point in the section of the grid model, the displacement and depth data of actual shale smearing on the section, and calculating the distribution thickness of the shale layer in each grid point along the actual shale smearing on the section and the section pressure, wherein the thickness of the shale layer in each grid point is determined according to the formation lithology data of a research area, and FIG. 5 is a schematic diagram of a lithology curve plate in the embodiment of the invention, and is obtained by loading a las format logging curve into professional logging interpretation software geoog.
S15: and calculating a three-dimensional section dredging coefficient according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point.
S16, when the three-dimensional section dredging coefficient is larger than a three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged, wherein the three-dimensional section dredging coefficient threshold value is determined according to two drilled broken block trapping, and according to drilling data, the key storage periods of the two drilled broken block trapping are chalk lines, are all dry wells, and all show good oil gas, so that the oil source of the area is sufficient. FIG. 6 is a graph of three-dimensional fracture surface drainage coefficient versus depth for a high-position oil-containing fault with three-dimensional fracture surface drainage coefficients above 5.85Mp.s, as shown by graph analysis, for three-hole wells with lengths 20, 19 and 2; the three-dimensional section dredging coefficient of the oil-containing control ring fault at the high position of the disfavored objective layer is below 5.85Mp.s. And determining that the three-dimensional section dredging coefficient threshold value of the high-position oil-containing control ring fault is 5.85Mp.s. Since the three-dimensional profile drainage coefficient threshold value is derived from a drilled reservoir, well drilling has been demonstrated and thus can represent the geological features of the target zone.
S17, dividing a three-dimensional section of a target area into class I faults with excellent dredge property, dividing the three-dimensional section of which the dredge coefficient C is larger than 15Mp.s and smaller than or equal to 15Mp.s into class II faults with excellent dredge property, dividing the faults with the three-dimensional section of which the dredge coefficient C is smaller than 10Mp.s and larger than 5.8Mp.s into class III faults with common dredge property, dividing the fault dredge property of which the three-dimensional section of which the dredge coefficient C is smaller than 5.8Mpa.s into class IV faults which are not dredged, wherein the class I faults control high-position trap formed by dredging, and oil gas is easy to move upwards across the lateral sides of the faults to form a gather pool which is the first deployment trap; the trapping times of II type fault control; the trap of the III-type fault control is a trap with high risk; the trap of the IV-class fault control is a fault which is not dredged, the oil gas is not easy to form aggregation across the fault, the trap cannot be formed at the high position of the oil gas, and drilling is not recommended. The detailed dredge quantitative evaluation criteria of the table 1 are shown, well positions are deployed according to the thought, risks are avoided, and reliable guidance is provided for exploration deployment and well drilling.
TABLE 1
In summary, in the method provided by the embodiment of the invention, section data and horizon data of a research area are obtained according to three-dimensional seismic data after the research area is stacked; 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; acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the cross section; according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient; and when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged. In the process, three-dimensional seismic data and logging information after the study area is overlapped are comprehensively considered, a three-dimensional geological model is finally established, after the grid model is obtained, the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point 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 of the study area is dredged according to the three-dimensional section dredging coefficient is more accurate.
The embodiment of the invention also provides a quantitative determination device for the three-dimensional fault guiding property, the principle of which is similar to that of a quantitative determination method for the three-dimensional fault guiding property, and the quantitative determination device is not repeated here.
Fig. 7 is a schematic diagram of a device for quantitatively determining three-dimensional fault diversion in an embodiment of the invention, as shown in fig. 7, the device includes:
the data obtaining module 701 is configured to obtain section data and horizon data of the research area according to the post-stack three-dimensional seismic data of the research area;
the three-dimensional geological model building module 702 is 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 gridding processing on a section in the three-dimensional geological model, so as to obtain a grid model;
a first calculation module 704, configured to obtain a thickness of a mudstone layer in each grid point in a section of the grid model, a displacement of actual mudstone smearing on the section, and depth data, and calculate a thickness of mudstone distribution and a section pressure of the mudstone layer in each grid point along the actual mudstone smearing displacement of the section;
a second calculating module 705, configured to calculate a three-dimensional section dredging coefficient according to a mud rock distribution thickness and a section pressure on a mud rock actual smearing displacement along a section in each grid point;
A dredge property determining module 706, configured to determine that the three-dimensional fault of the investigation region is dredged when the three-dimensional section dredging coefficient is greater than the three-dimensional section dredging coefficient threshold, and otherwise determine that the three-dimensional fault of the investigation region is not dredged.
In an embodiment, the logging information includes at least one of shale content data, gamma data, acoustic data, and resistivity data.
In one embodiment, the three-dimensional geologic model creation module 702 includes:
a horizon model building module 7021, configured to build a horizon model according to horizon data;
the section model building module 7022 is used for building a fault model according to section data;
a correction module 7023 for correcting the horizon model and the fault model based on the logging information;
the generating module 7024 is configured to process the intersection relationship of the horizon and the section according to the corrected horizon model and the corrected section model, so as to form a three-dimensional geological model including the horizon and the section.
In one embodiment, horizon modeling module 7021 is specifically configured to:
constructing a horizon construction surface model according to horizon data;
analyzing the relation between upper and lower adjacent layers in the layer structure surface model in a three-dimensional space, removing layer malformation points causing strings or intersections, and obtaining a new layer structure surface model;
And carrying out smoothing treatment on the new horizon construction surface model to obtain a horizon model.
In one embodiment, the section model building module 7022 is specifically configured to:
removing abnormal data points in the section data to obtain edge cutting data, wherein the edge cutting data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault edge data;
and analyzing the connection relation of the fault surface model interruption surface, and correcting the part of the fault surface model which does not meet the preset requirement to obtain the fault model.
In one embodiment, the correction module 7023 is specifically configured to:
acquiring uphole layered system data according to logging information;
correcting the horizon model by using the data of the layering system on the well 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 displacement of the actual mudstone smearing on the section in each grid point according to the inclination angle and the breaking distance in each grid point.
In an embodiment, the apparatus further comprises a mud layer thickness obtaining module 708 for:
obtaining stratum lithology data of the research area according to logging information of the research area;
And obtaining the thickness of the shale layer in each grid point in the section of the grid model according to the stratum lithology data.
In one embodiment, the first computing module 704 is specifically configured to:
the following formula is adopted, and according to the thickness of the shale layer in each grid point in the section of the grid model and the actual displacement of the shale smearing on the section, the distribution thickness of the shale layer in each grid point along the actual displacement of the shale smearing on the section is calculated:
L i ＝H i /S i
wherein L is i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; h i Is the mud layer thickness in the ith grid point; s is S i The displacement of the actual mudstone smearing on the section;
the section pressure in each grid point is calculated from the depth data in each grid point using the following formula:
P i ＝10 -3 M i (ρ l -ρ w )·g·cosa
wherein P is i Is the section pressure in the ith grid point; m is M i Depth data within the ith grid point; ρ l Average density for overburden; ρ w Is the average density of the formation water; g is gravity acceleration; a is the dip in the ith grid point.
In one embodiment, the second computing module 705 is specifically configured to:
the three-dimensional section dredging coefficient is calculated according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section by adopting the following formula:
Wherein C is a three-dimensional section dredging coefficient; l (L) i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; p (P) i Is the section pressure in the ith grid point.
In summary, in the device provided by the embodiment of the invention, section data and horizon data of a research area are obtained according to three-dimensional seismic data after the research area is stacked; 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; acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the cross section; according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient; and when the three-dimensional section dredging coefficient is larger than the three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged. In the process, three-dimensional seismic data and logging information after the study area is overlapped are comprehensively considered, a three-dimensional geological model is finally established, after the grid model is obtained, the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point 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 of the study area is dredged according to the three-dimensional section dredging coefficient is more accurate.
An embodiment of the present application further provides a computer device, and fig. 8 is a schematic diagram of the computer device in the embodiment of the present application, where the computer device can implement all the steps in the quantitative determination method of three-dimensional fault breakout 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;
wherein the processor 801, the memory 802, and the communication interface 803 complete communication with each other through the communication bus 804; the communication interface 803 is configured to implement information transmission between related devices such as a server device, a detection device, and a user device;
the processor 801 is configured to invoke a computer program in the memory 802, and when the processor executes the computer program, the processor implements all the steps in the quantitative determination method of three-dimensional fault breakout in the above embodiment.
An embodiment of the present application also provides a computer-readable storage medium, which can implement all the steps in the quantitative determination method of three-dimensional fault breakout in the above embodiment, and on which a computer program is stored, which when executed by a processor, implements all the steps in the quantitative determination method of three-dimensional fault breakout in the above embodiment.
It will be appreciated by those skilled in the art that 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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 foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (18)
1. A method for quantitatively determining three-dimensional fault grooming, comprising:
acquiring section data and horizon data of the research area according to the three-dimensional seismic data after the research area is overlapped;
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;
acquiring the thickness of the shale layer in each grid point in the cross section of the grid model, the actual mudstone daubing displacement and depth data on the cross section, and calculating the distribution thickness of the mudstone and the cross section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the cross section;
according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer along the section in each grid point, calculating a three-dimensional section dredging coefficient;
when the three-dimensional section dredging coefficient is larger than a three-dimensional section dredging coefficient threshold value, determining that the three-dimensional fault of the research area is dredged, otherwise, determining that the three-dimensional fault of the research area is not dredged;
acquiring the thickness of the shale layer in each grid point in the section of the grid model, the actual mudstone daubing displacement and depth data on the section, and calculating the distribution thickness of the mudstone and the section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the section, wherein the method comprises the following steps:
The following formula is adopted, and according to the thickness of the shale layer in each grid point in the section of the grid model and the actual displacement of the shale smearing on the section, the distribution thickness of the shale layer in each grid point along the actual displacement of the shale smearing on the section is calculated:
L i ＝H i /S i
wherein L is i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; h i Is the mud layer thickness in the ith grid point; s is S i The displacement of the actual mudstone smearing on the section;
the section pressure in each grid point is calculated from the depth data in each grid point using the following formula:
P i ＝10 -3 M i (ρ l -ρ w )·g·cosa
wherein P is i Is the section pressure in the ith grid point; m is M i Depth data within the ith grid point; ρ l Average density for overburden; ρ w Is the average density of the formation water; g is gravity acceleration; a is the dip in the ith grid point;
the three-dimensional section dredging coefficient is calculated according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section by adopting the following formula:
wherein C is a three-dimensional section dredging coefficient; l (L) i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; p (P) i Is the section pressure in the ith grid point.
2. The method of quantitative determination of three-dimensional fault diversion of claim 1, wherein the logging information comprises at least one of argillaceous content data, gamma data, sonic data, and resistivity data.
3. The method of quantitative determination of three-dimensional fault grooming as claimed in claim 1, wherein establishing a three-dimensional geologic model from the section data, horizon data and logging information comprises:
establishing a horizon model according to 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 intersection relation of the horizon and the section according to the corrected horizon model and the corrected fault model to form a three-dimensional geological model containing the horizons and the sections.
4. The quantitative determination method of three-dimensional fault grooming as claimed in claim 3, wherein establishing a horizon model from horizon data comprises:
constructing a horizon construction surface model according to horizon data;
analyzing the relation between upper and lower adjacent layers in the layer structure surface model in a three-dimensional space, removing layer malformation points causing strings or intersections, and obtaining a new layer structure surface model;
And carrying out smoothing treatment on the new horizon construction surface model to obtain a horizon model.
5. The method for quantitatively determining three-dimensional fault grooming as in claim 3, wherein building a fault model from the profile data comprises:
removing abnormal data points in the section data to obtain edge cutting data, wherein the edge cutting data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault edge data;
and analyzing the connection relation of the fault surface model interruption surface, and correcting the part of the fault surface model which does not meet the preset requirement to obtain the fault model.
6. The method of quantitative determination of three-dimensional fault grooming as claimed in claim 3, wherein correcting the horizon model and the fault model based on the logging information comprises:
acquiring uphole layered system data according to logging information;
correcting the horizon model by using the data of the layering system on the well to obtain a corrected horizon model;
and correcting the fault model by using the corrected horizon model.
7. The method for quantitatively determining three-dimensional fault grooming as in claim 1, further comprising:
and calculating the displacement of the actual mudstone smearing on the section in each grid point according to the inclination angle and the breaking distance in each grid point.
8. The method for quantitatively determining three-dimensional fault grooming as in claim 1, further comprising:
obtaining stratum lithology data of the research area according to logging information of the research area;
and obtaining the thickness of the shale layer in each grid point in the section of the grid model according to the stratum lithology data.
9. A quantitative determination device for three-dimensional fault grooming, comprising:
the data acquisition module is used for acquiring section data and horizon data of the research area according to the three-dimensional seismic data after the research area is overlapped;
the three-dimensional geological model building module is used for building a three-dimensional geological model according to the section data, the horizon data and the logging information of the research area;
the grid model obtaining module is used for carrying out gridding treatment on the section in the three-dimensional geological model to obtain a grid model;
the first calculation module is used for obtaining the thickness of the shale layer in each grid point in the section of the grid model, the actual mudstone daubing displacement and depth data on the section, and calculating the distribution thickness of the mudstone and the section pressure of the shale layer in each grid point along the actual mudstone daubing displacement of the section;
the second calculation module is used for calculating a three-dimensional section dredging coefficient according to the mud rock distribution thickness and the section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section;
The dredging property determining module is used for determining that the three-dimensional fault of the research area is dredged when the three-dimensional section dredging coefficient is larger than a three-dimensional section dredging coefficient threshold value, otherwise, determining that the three-dimensional fault of the research area is not dredged;
the first computing module is specifically configured to:
the following formula is adopted, and according to the thickness of the shale layer in each grid point in the section of the grid model and the actual displacement of the shale smearing on the section, the distribution thickness of the shale layer in each grid point along the actual displacement of the shale smearing on the section is calculated:
L i ＝H i /S i
wherein L is i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; h i Is the mud layer thickness in the ith grid point; s is S i The displacement of the actual mudstone smearing on the section;
the section pressure in each grid point is calculated from the depth data in each grid point using the following formula:
P i ＝10 -3 M i (ρ l -ρ w )·g·cosa
wherein P is i Is the section pressure in the ith grid point; m is M i Depth data within the ith grid point; ρ l Average density for overburden; ρ w Is the average density of the formation water; g is gravity acceleration; a is the dip in the ith grid point;
the second calculation module is specifically configured to:
the three-dimensional section dredging coefficient is calculated according to the mud rock distribution thickness and section pressure on the actual smearing displacement of the mud rock layer in each grid point along the section by adopting the following formula:
Wherein C is a three-dimensional section dredging coefficient; l (L) i The mud rock distribution thickness on the actual smearing displacement of the mud rock layer in the ith grid point along the section is obtained; p (P) i Is the section pressure in the ith grid point.
10. The quantitative determination apparatus of three-dimensional fault diversion of claim 9, wherein the logging information comprises at least one of shale content data, gamma data, acoustic data, and resistivity data.
11. The quantitative determination apparatus of three-dimensional fault grooming as claimed in claim 9, wherein the three-dimensional geologic model building module comprises:
the horizon model building module is used for building a horizon model according to horizon data;
the section model building module is used for building a fault model according to the section data;
the correction module is used for correcting the horizon model and the fault model based on logging information;
and the generating module is used for processing the intersection relation of the horizon and the section according to the corrected horizon model and the corrected fault model to form a three-dimensional geological model containing the horizon and the section.
12. The quantitative determination device of three-dimensional fault grooming according to claim 11, wherein the horizon model building module is specifically configured to:
Constructing a horizon construction surface model according to horizon data;
analyzing the relation between upper and lower adjacent layers in the layer structure surface model in a three-dimensional space, removing layer malformation points causing strings or intersections, and obtaining a new layer structure surface model;
and carrying out smoothing treatment on the new horizon construction surface model to obtain a horizon model.
13. The quantitative determination device for three-dimensional fault diversion of claim 11, wherein the section model building module is specifically configured to:
removing abnormal data points in the section data to obtain edge cutting data, wherein the edge cutting data comprises fault line data and fault point composition data;
generating a fault plane model according to the fault edge data;
and analyzing the connection relation of the fault surface model interruption surface, and correcting the part of the fault surface model which does not meet the preset requirement to obtain the fault model.
14. The quantitative determination device of three-dimensional fault grooming according to claim 11, wherein the correction module is specifically configured to:
acquiring uphole layered system data according to logging information;
correcting the horizon model by using the data of the layering system on the well to obtain a corrected horizon model;
and correcting the fault model by using the corrected horizon model.
15. The quantitative determination device of three-dimensional fault grooming as in claim 9, further comprising a third calculation module for:
and calculating the displacement of the actual mudstone smearing on the section in each grid point according to the inclination angle and the breaking distance in each grid point.
16. The quantitative determination device for three-dimensional fault diversion of claim 9, further comprising a mud layer thickness obtaining module for:
obtaining stratum lithology data of the research area according to logging information of the research area;
and obtaining the thickness of the shale layer in each grid point in the section of the grid model according to the stratum lithology data.
17. 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 8 when executing the computer program.
18. 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 8.
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| CN105089615A (en) * | 2014-05-16 | 2015-11-25 | 中国石油化工股份有限公司 | Log data historical retrogression treatment method based on oil reservoir model |
| CN108508484A (en) * | 2018-02-23 | 2018-09-07 | 中国石油大学(华东) | A kind of evaluation method suitable for tension-shear fault mudstone creep effect |
| CN110321595A (en) * | 2019-06-06 | 2019-10-11 | 中国石油大学(华东) | The Fault closeness evaluation method of static factor of merit is extracted in a kind of well logging |
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