CN114218787A - Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics - Google Patents
Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics Download PDFInfo
- Publication number
- CN114218787A CN114218787A CN202111513975.0A CN202111513975A CN114218787A CN 114218787 A CN114218787 A CN 114218787A CN 202111513975 A CN202111513975 A CN 202111513975A CN 114218787 A CN114218787 A CN 114218787A
- Authority
- CN
- China
- Prior art keywords
- rock
- research area
- dimensional
- fracture
- ancient
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000011160 research Methods 0.000 claims abstract description 65
- 239000011435 rock Substances 0.000 claims abstract description 62
- 230000000694 effects Effects 0.000 claims abstract description 22
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 12
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 230000006837 decompression Effects 0.000 claims abstract description 8
- 238000004134 energy conservation Methods 0.000 claims abstract description 8
- 230000008569 process Effects 0.000 claims abstract description 8
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 7
- 238000011084 recovery Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 30
- 230000003068 static effect Effects 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 239000004576 sand Substances 0.000 claims description 6
- 238000004215 lattice model Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 238000005336 cracking Methods 0.000 claims description 3
- 239000012530 fluid Substances 0.000 claims description 3
- 239000007787 solid Substances 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 claims description 2
- 238000011161 development Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Geometry (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Life Sciences & Earth Sciences (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Agronomy & Crop Science (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Remote Sensing (AREA)
- Pure & Applied Mathematics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geophysics (AREA)
- Computer Graphics (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention provides a fault-related fracture quantitative prediction method based on four-dimensional geomechanics, which is suitable for the fields of oil-gas geology and tectonic geology. Collecting geological basic data and related data of a research area, and constructing a current three-dimensional geological model of the research area by using the related data; then, introducing a decompression coefficient in the concept of increasing the time dimension in the three-dimensional geological model to consider the decompression effect in the stratum recovery deformation process; acquiring stress magnitude and direction information of secondary structures in different key periods by deducing fault activity and related crack formation information in a current three-dimensional geological model and combining quantitative analysis and evolution history analysis of the structure of a research area; reconstructing the cracks to form an ancient structure framework and an ancient ground stress field of an evolution key stage, constructing the relation between the ancient ground stress fields of different key stages and crack parameters, and quantitatively predicting related cracks of the faults by combining a rock fracture criterion and energy conservation. The method has simple steps and good prediction effect.
Description
Technical Field
The invention relates to a quantitative prediction method for fault-related fractures, which is particularly suitable for the fields of oil-gas geology and tectonic geology.
Background
In areas with complex structures, fractures related to faults have important influence on oil gas enrichment and development. The fractures can be used as important oil and gas storage spaces and key channels for oil and gas migration. The cracks have a communicating effect on the dispersed and isolated pores in the reservoir, so that the effective porosity is increased, and the permeability is improved. Identification, accurate description and semi-quantitative research of fractures are the key points for effective development of fractured oil and gas reservoirs. The fracture study may be developed based on data such as outcrop, core, well logging, and earthquake. Crack formation and formation evolution are closely indistinguishable, and as a formation develops, different types of cracks are formed or derived. The development distribution of the fracture related to the fault is related to multiple factors such as a ground stress field, the structural activity period, rock properties and the like, and the development of the analysis and prediction of the fracture related to the fault is important for the oil-gas exploration and development of the structural complex region.
The invention patent with application publication number CN112731556A provides a crack development area prediction method and a computer storage medium for predicting the crack development area, and the crack semi-quantitative prediction is carried out on the basis of analysis of rock cores and seismic data; the invention patent with application publication number CN111239849A provides a reservoir fracture prediction method and a prediction system based on stress release, and the method and the system sequentially carry out coring research, well logging interpretation and geological modeling through a fracture evaluation module to realize the analysis of the development condition of all-round fractures; the invention patent with application publication number CN112394408A provides an anisotropic medium crack prediction method and device, and the processing efficiency, the automation degree and the accuracy of the anisotropic medium crack prediction process are effectively improved based on the interpretation and analysis of a seismic data body.
However, the fracture prediction patents or methods, including the above inventions, are based on geometric, kinematic or seismic interpretation methods, and do not show the multiple stages of the formation and development of the structure, nor do they reveal the mechanical nature of the evolution of the fracture formation. In a structural complex area, the crack prediction goodness of fit is low.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a fault related crack quantitative prediction method based on four-dimensional geomechanics, which has scientific principle and high prediction result goodness of fit, and the core is as follows: and (3) considering the decompacting effect of stratum recovery, and establishing the relation between the paleo-earth stress field and the crack parameters on the basis of forming the evolutionary paleo-structure framework and the paleo-earth stress field by the secondary cracks in the three-dimensional reconstruction key period.
In order to achieve the aim, the invention provides a fault related crack quantitative prediction method based on four-dimensional geomechanics, which sets a research area aiming at the fields of oil-gas geology and tectonic geology, collects geological basic data and related data of the research area, and constructs a current three-dimensional geological model of the research area by using the related data; then on the basis of the construction of the three-dimensional geological model, adding a concept of time dimension, introducing and setting a decompression solid coefficient, and considering the decompression effect in the stratum recovery deformation process; carrying out experimental detection by deducing fault activity and related crack formation information in the current three-dimensional geological model, and acquiring stress magnitude and direction information of the secondary ancient structures in different key periods by combining quantitative analysis and evolution history analysis of the structures in a research area; reconstructing the cracks to form an ancient structure framework and an ancient ground stress field of an evolution key stage, constructing the relation between the ancient ground stress fields of different key stages and crack parameters, and quantitatively predicting related cracks of the faults by combining a rock fracture criterion and energy conservation.
The method comprises the following specific steps:
step one, collecting geological basic data and related data of a research area, and establishing a current three-dimensional geometric model of the research area on the basis;
secondly, collecting a target layer rock sample in a research area, detecting the target layer rock sample by utilizing a true triaxial mechanical test, and obtaining the static Young modulus E of the rock samplesAnd poisson ratio musCalculating the dynamic Young's modulus E of the rock by using the logging informationdAnd poisson ratio mudOn the basis, a static Young's modulus E of the rock sample is establishedsAnd dynamic Young's modulus EdQuantitative relationship between them, Poisson's ratio mu of rock samplesTo dynamic Poisson ratio mudThe quantitative relationship is established, and a three-dimensional static rock mechanical field of a target layer of the research area is established by an interpolation method, so that a present three-dimensional geological model of the research area is formed;
wherein the dynamic Young's modulus E of the rockdThe calculation formula is as follows:
in the formula: edIs the dynamic Young's modulus of the rock, ρ is the rock density, Δ tsFor transverse wave time difference, Δ tpBeta is a unit conversion coefficient;
dynamic Poisson's ratio mu of rockdThe calculation formula is as follows:
in the formula: mu.sdIs the dynamic Poisson's ratio of rock, Δ tsFor transverse wave time difference, Δ tpIs the longitudinal wave time difference;
thirdly, on the basis of a geomechanics principle, following the principle of volume conservation of a geologic body before and after fault activity, fully considering the stratum decompaction effect in the process of restoring and deforming the current three-dimensional geological model on the basis of the current three-dimensional geological model of a research area, setting a decompaction coefficient gamma of the stratum when the stratum is stripped layer by layer, realizing geological restoration of the current three-dimensional geological model by changing the internal parameters of the current three-dimensional geological model and stripping the stratum layer by layer, and reconstructing cracks to form an ancient structural grid model with an evolution key period;
step four, respectively carrying out year-fixed detection, acoustic emission detection and viscous remanence detection on the ancient structural grid model, and determining key stages of fault activity and related crack formation in the research region and ancient structural stress and direction information of the research region in different key stages by combining quantitative analysis and evolution history analysis of the structure of the research region on the basis of a detection result;
step five, respectively constructing three-dimensional geomechanical models corresponding to different key stages of a target layer of the research area by using the ancient structural lattice models of different key stages reconstructed in the step three and the step four and ancient structural stress magnitude and direction data, so as to quantitatively represent the ancient ground stress fields of the research area at different key stages;
step six, comprehensively considering rock fracture criteria and energy conservation, and establishing a relational expression S between the sub-paleoid stress fields and the fracture parameters of different key periods of the research areai＝g(p1i,p2iV.) wherein: g represents a functional relationship, i represents different key stages, SiRepresents the i-th paleo-ground stress field, p1iAnd p2iParameters representing different i-th fractures;
wherein the rock fracture criteria include:
fracture criteria for shear fracture
Cracking criterion T of opening seamo＝τm-σm–C/2，
Criterion for rupture of closed seam Tc≈σ1In the formula: s is the rock shear fracture strength, τmFor maximum shear stress, the value is (σ)1-σ3)/2，σmIs a positive stress, and has a value of (σ)1+σ3)/2，σ1And σ3Respectively a maximum principal stress and a minimum principal stress,
is an internal angle of friction, ToRock tensile strength, C cohesion, TcRepresenting the compressive strength of the rock;
the conservation of energy is expressed in the amount of energy (E) required to generate the cracks2) Energy value (E) associated with loss of geologic body1) Equal, i.e. E1＝E2。
Seventhly, obtaining paleo-earth stress field values of different key stages from the three-dimensional geomechanical models corresponding to different key stages of the constructed target layer of the research area, and converting the paleo-earth stress field values into fracture parameter values p by using a relational expression between the paleo-earth stress field and the fracture parameters1i,p2iV. will crack parameter p1i,p2iAnd overlapping the two sections according to a time sequence to obtain a quantitative prediction model F ═ sigma beta of the crack in the research areai·(p1i,p2iV.) wherein: f is the crack prediction result, betaiIs a weight coefficient, betai＝σ1i/∑σ1iI denotes the different critical periods, σ1iAnd (4) representing the maximum principal stress of the ith stage, and utilizing a research area crack quantitative prediction model to realize quantitative prediction of the research area crack.
Further, the static Young modulus and the Poisson ratio of the rock in the second step are average values of the mechanical experiment results of the plurality of groups of three-axis rocks; the interpolation method is preferably the Kriging method.
Further, the annual inspection in step fourThe detection can be fluid inclusion dating detection, K-Ar dating detection,40Ar-39Any one or more of Ar isotope dating detection, Rb-Sr dating detection and U-Th dating detection.
Further, the fracture parameters in the sixth step include fracture density, fracture strike and fracture dip.
Has the advantages that: the method comprehensively considers the decompacting effect of stratum recovery, sets the decompacting coefficient gamma of the stratum when the stratum is stripped layer by layer, realizes the geological recovery of the current three-dimensional geological model through the change of parameters in the model and the stripping of the stratum layer by layer, reconstructs the cracks to form an ancient structural lattice model with an evolution key stage, establishes the relation between an ancient structural stress field and crack parameters on the basis of the ancient structural lattice and the ancient structural stress field which are evolved by the cracks in the three-dimensional reconstruction key stage, realizes the quantitative prediction of related cracks of the faults on the basis of rock fracture criteria and energy conservation, and has scientific principle, high coincidence rate and good reliability of prediction results.
Drawings
FIG. 1 is a technical flow chart of the fault-related fracture quantitative prediction method based on four-dimensional geomechanics of the present invention.
Detailed Description
The embodiments of the present invention will be further explained with reference to the drawings
As shown in FIG. 1, the method for quantitatively predicting the related fracture of the fault based on the four-dimensional geomechanics sets a research area aiming at the fields of oil-gas geology and tectonic geology, collects geological basic data and related data of the research area, and constructs a current three-dimensional geological model of the research area by using the related data; then on the basis of the construction of the three-dimensional geological model, adding a concept of time dimension, introducing and setting a decompression solid coefficient, and considering the decompression effect in the stratum recovery deformation process; carrying out experimental detection by deducing fault activity and related crack formation information in the current three-dimensional geological model, and acquiring stress magnitude and direction information of the secondary ancient structures in different key periods by combining quantitative analysis and evolution history analysis of the structures in a research area; reconstructing the cracks to form an ancient structure framework and an ancient ground stress field of an evolution key stage, constructing the relation between the ancient ground stress fields of different key stages and crack parameters, and quantitatively predicting related cracks of the faults by combining a rock fracture criterion and energy conservation.
The method comprises the following specific steps:
step one, collecting geological basic data and related data of a research area, and establishing a current three-dimensional geometric model of the research area on the basis;
secondly, collecting a target layer rock sample in a research area, detecting the target layer rock sample by utilizing a true triaxial mechanical test, and obtaining the static Young modulus E of the rock samplesAnd poisson ratio musCalculating the dynamic Young's modulus E of the rock by using the logging informationdAnd poisson ratio mudOn the basis, a static Young's modulus E of the rock sample is establishedsAnd dynamic Young's modulus EdQuantitative relationship between them, Poisson's ratio mu of rock samplesTo dynamic Poisson ratio mudThe quantitative relationship is established, and a three-dimensional static rock mechanical field of a target layer of a research area is constructed by a Kriging interpolation method, so that a present three-dimensional geological model of the research area is formed;
wherein the dynamic Young's modulus E of the rockdThe calculation formula is as follows:
in the formula: edIs the dynamic Young's modulus of the rock, ρ is the rock density, Δ tsFor transverse wave time difference, Δ tpBeta is a unit conversion coefficient;
dynamic Poisson's ratio mu of rockdThe calculation formula is as follows:
in the formula: mu.sdIs the dynamic Poisson's ratio of rock, Δ tsFor transverse wave time difference, Δ tpIs the longitudinal wave time difference;
thirdly, on the basis of a geomechanics principle, following the principle of volume conservation of a geologic body before and after fault activity, fully considering the stratum decompaction effect in the process of restoring and deforming the current three-dimensional geological model on the basis of the current three-dimensional geological model of a research area, setting a decompaction coefficient gamma of the stratum when the stratum is stripped layer by layer, realizing geological restoration of the current three-dimensional geological model by changing the internal parameters of the current three-dimensional geological model and stripping the stratum layer by layer, and reconstructing cracks to form an ancient structural grid model with an evolution key period;
step four, respectively carrying out year-fixed detection, acoustic emission detection and viscous remanence detection on the ancient structural grid model, and determining key stages of fault activity and related crack formation in the research region and ancient structural stress and direction information of the research region in different key stages by combining quantitative analysis and evolution history analysis of the structure of the research region on the basis of a detection result; the dating detection is fluid inclusion dating test detection, K-Ar dating detection,40Ar-39Any one or more of Ar isotope dating detection, Rb-Sr dating detection and U-Th dating detection.
Step five, respectively constructing three-dimensional geomechanical models corresponding to different key stages of a target layer of the research area by using the ancient structural lattice models of different key stages reconstructed in the step three and the step four and ancient structural stress magnitude and direction data, so as to quantitatively represent the ancient ground stress fields of the research area at different key stages;
step six, comprehensively considering rock fracture criteria and energy conservation, and establishing a relational expression S between the sub-paleoid stress fields and the fracture parameters of different key periods of the research areai＝g(p1i,p2iV.) wherein: g represents a functional relationship, i represents different key stages, SiRepresents the i-th paleo-ground stress field, p1iAnd p2iParameters representing different i-th fractures; the fracture parameters comprise fracture density, fracture strike and fracture dip;
wherein the rock fracture criteria include:
fracture criteria for shear fracture
Cracking criterion T of opening seamo＝τm-σm–C/2，
Criterion for rupture of closed seam Tc≈σ1In the formula: s is the rock shear fracture strength, τmFor maximum shear stress, the value is (σ)1-σ3)/2，σmIs a positive stress, and has a value of (σ)1+σ3)/2，σ1And σ3Respectively a maximum principal stress and a minimum principal stress,
is an internal angle of friction, ToRock tensile strength, C cohesion, TcRepresenting the compressive strength of the rock;
the conservation of energy is expressed in the amount of energy (E) required to generate the cracks2) Energy value (E) associated with loss of geologic body1) Equal, i.e. E1＝E2。
Seventhly, obtaining paleo-earth stress field values of different key stages from the three-dimensional geomechanical models corresponding to different key stages of the constructed target layer of the research area, and converting the paleo-earth stress field values into fracture parameter values p by using a relational expression between the paleo-earth stress field and the fracture parameters1i,p2iV. will crack parameter p1i,p2iAnd overlapping the two sections according to a time sequence to obtain a quantitative prediction model F ═ sigma beta of the crack in the research areai·(p1i,p2iV.) wherein: f is the crack prediction result, betaiIs a weight coefficient, betai＝σ1i/∑σ1iI denotes the different critical periods, σ1iAnd (4) representing the maximum principal stress of the ith stage, and utilizing a research area crack quantitative prediction model to realize quantitative prediction of the research area crack.
Claims (5)
1. A fault-related fracture quantitative prediction method based on four-dimensional geomechanics is characterized by comprising the following steps: setting a research area aiming at the fields of oil-gas geology and tectonic geology, collecting geological basic data and related data of the research area, and constructing a current three-dimensional geological model of the research area by using the related data; then on the basis of the construction of the three-dimensional geological model, adding a concept of time dimension, introducing and setting a decompression solid coefficient, and considering the decompression effect in the stratum recovery deformation process; carrying out experimental detection by deducing fault activity and related crack formation information in the current three-dimensional geological model, and acquiring stress magnitude and direction information of the secondary ancient structures in different key periods by combining quantitative analysis and evolution history analysis of the structures in a research area; reconstructing the cracks to form an ancient structure framework and an ancient ground stress field of an evolution key stage, constructing the relation between the ancient ground stress fields of different key stages and crack parameters, and quantitatively predicting related cracks of the faults by combining a rock fracture criterion and energy conservation.
2. The quantitative prediction method for fault-related fractures based on four-dimensional geomechanics according to claim 1 is characterized by comprising the following specific steps:
step one, collecting geological basic data and related data of a research area, and establishing a current three-dimensional geometric model of the research area on the basis;
secondly, collecting a target layer rock sample in a research area, detecting the target layer rock sample by utilizing a true triaxial mechanical test, and obtaining the static Young modulus E of the rock samplesAnd poisson ratio musCalculating the dynamic Young's modulus E of the rock by using the logging informationdAnd poisson ratio mudOn the basis, a static Young's modulus E of the rock sample is establishedsAnd dynamic Young's modulus EdQuantitative relationship between them, Poisson's ratio mu of rock samplesTo dynamic Poisson ratio mudThe quantitative relationship is established, and a three-dimensional static rock mechanical field of a target layer of the research area is established by an interpolation method, so that a present three-dimensional geological model of the research area is formed;
wherein the dynamic Young's modulus E of the rockdThe calculation formula is as follows:
in the formula: edIs the dynamic Young's modulus of the rock, ρ is the rock density, Δ tsAs a transverse wave time difference，ΔtpBeta is a unit conversion coefficient;
dynamic Poisson's ratio mu of rockdThe calculation formula is as follows:
in the formula: mu.sdIs the dynamic Poisson's ratio of rock, Δ tsFor transverse wave time difference, Δ tpIs the longitudinal wave time difference;
thirdly, on the basis of a geomechanics principle, following the principle of volume conservation of a geologic body before and after fault activity, fully considering the stratum decompaction effect in the process of restoring and deforming the current three-dimensional geological model on the basis of the current three-dimensional geological model of a research area, setting a decompaction coefficient gamma of the stratum when the stratum is stripped layer by layer, realizing geological restoration of the current three-dimensional geological model by changing the internal parameters of the current three-dimensional geological model and stripping the stratum layer by layer, and reconstructing cracks to form an ancient structural grid model with an evolution key period;
step four, respectively carrying out year-fixed detection, acoustic emission detection and viscous remanence detection on the ancient structural grid model, and determining key stages of fault activity and related crack formation in the research region and ancient structural stress and direction information of the research region in different key stages by combining quantitative analysis and evolution history analysis of the structure of the research region on the basis of a detection result;
step five, respectively constructing three-dimensional geomechanical models corresponding to different key stages of a target layer of the research area by using the ancient structural lattice models of different key stages reconstructed in the step three and the step four and ancient structural stress magnitude and direction data, so as to quantitatively represent the ancient ground stress fields of the research area at different key stages;
step six, comprehensively considering rock fracture criteria and energy conservation, and establishing a relational expression S between the sub-paleoid stress fields and the fracture parameters of different key periods of the research areai＝g(p1i,p2i…), wherein: g represents a functional relationship, i represents different key stages, SiRepresents the i-th paleo-ground stress field, p1iAnd p2iParameters representing different i-th fractures;
wherein the rock fracture criteria include:
fracture criteria for shear fracture
Cracking criterion T of opening seamo＝τm-σm–C/2，
Criterion for rupture of closed seam Tc≈σ1，
In the formula: s is the rock shear fracture strength, τmFor maximum shear stress, the value is (σ)1-σ3)/2，σmIs a positive stress, and has a value of (σ)1+σ3)/2，σ1And σ3Respectively a maximum principal stress and a minimum principal stress,
is an internal angle of friction, ToRock tensile strength, C cohesion, TcRepresenting the compressive strength of the rock;
the conservation of energy is represented by the amount of energy E required to produce the crack2Energy value E related to geologic body loss1Equal, i.e. E1＝E2。
Seventhly, obtaining paleo-earth stress field values of different key stages from the three-dimensional geomechanical models corresponding to different key stages of the constructed target layer of the research area, and converting the paleo-earth stress field values into fracture parameter values p by using a relational expression between the paleo-earth stress field and the fracture parameters1i,p2i…, the crack parameter p1i,p2i…, overlapping according to time sequence to obtain the research area crack quantitative prediction model F ═ sigma betai·(p1i,p2i…), wherein: f is the crack prediction result, betaiIs a weight coefficient, betai＝σ1i/∑σ1iI denotes the different critical periods, σ1iAnd (4) representing the maximum principal stress of the ith stage, and utilizing a research area crack quantitative prediction model to realize quantitative prediction of the research area crack.
3. The method for quantitatively predicting fault-related fractures based on four-dimensional geomechanics according to claim 2, wherein: the static Young modulus and the Poisson ratio of the rock in the second step are average values of the mechanical experiment results of the plurality of groups of triaxial rocks; the interpolation method is preferably the Kriging method.
4. The method for quantitatively predicting fault-related fractures based on four-dimensional geomechanics according to claim 2, wherein: the dating test in the fourth step can be a fluid inclusion dating test, a K-Ar dating test, a,40Ar-39Any one or more of Ar isotope dating detection, Rb-Sr dating detection and U-Th dating detection.
5. The method of claim 2, wherein the fracture parameters of the six steps include fracture density, fracture strike, and fracture dip.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111513975.0A CN114218787A (en) | 2021-12-10 | 2021-12-10 | Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111513975.0A CN114218787A (en) | 2021-12-10 | 2021-12-10 | Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114218787A true CN114218787A (en) | 2022-03-22 |
Family
ID=80701069
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111513975.0A Pending CN114218787A (en) | 2021-12-10 | 2021-12-10 | Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114218787A (en) |
-
2021
- 2021-12-10 CN CN202111513975.0A patent/CN114218787A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11668853B2 (en) | Petrophysical inversion with machine learning-based geologic priors | |
| EP3298437B1 (en) | Inversion for tectonic stress | |
| CN105319603A (en) | Compact sandstone reservoir complex netted fracture prediction method | |
| CN113534291A (en) | Quantitative prediction method for different-scale fractures of low-permeability reservoir under constraint of rock mechanical layer | |
| CN112502701B (en) | Classification evaluation method for comprehensive geology-engineering of low-permeability reservoir | |
| CN104331745A (en) | Period-divided and reason-divided prediction evaluation method of natural fracture in gas reservoir | |
| CN113820750A (en) | Method for quantitatively predicting mudstone structural cracks based on elastoplasticity mechanics | |
| CN105549068A (en) | 3D anisotropic micro seismic interference inverse positioning method and 3D anisotropic micro seismic interference inverse positioning system | |
| CN115017833B (en) | High-ground-stress soft rock body ground stress calculation method based on deep neural network | |
| van-der-Zee et al. | 3D geomechanical modeling of complex salt structures | |
| CN114755310A (en) | Method for predicting evolution rule of rock mechanics layer of fractured reservoir | |
| CN115166853A (en) | Shale gas reservoir natural fracture model establishing method and device, electronic equipment and medium | |
| Song et al. | Prediction and analysis of geomechanical properties of jimusaer shale using a machine learning approach | |
| Li et al. | Paleotectonic stress field modeling and fracture prediction of the Longmaxi Formation in the N216 well block, southern Sichuan Basin, China | |
| US20240134080A1 (en) | Method and System for Real-Time Calculating a Microseismic Focal Mechanism Based on Deep Learning | |
| Gupta et al. | A Machine Learning based proxy model for the rapid prediction of hydraulic fractures | |
| CN114218787A (en) | Quantitative prediction method for fault-related fractures based on four-dimensional geomechanics | |
| Sarkheil et al. | The fracture network modeling in naturally fractured reservoirs using artificial neural network based on image loges and core measurements | |
| CN113108957B (en) | Rock core testing and extracting method for paleotectonic period ground stress | |
| Lacazette et al. | Geomechanical and flow simulation of hydraulic fractures using high-resolution passive seismic images | |
| US20240103036A1 (en) | Embedded artificial intelligence augmented sensors | |
| Zhang et al. | Application of computational intelligence method in petroleum geomechanics characterization | |
| Lei et al. | A New DFM Dynamic Modeling Workflow Through a Non-Intrusive EDFM Method to Quickly Calibrate Fracture Model With Production Data: Practical Application on a Granite Reservoir Case | |
| Thompson et al. | Investigation of the Synthetic Rock Mass approach for the consideration of reservoir behavior | |
| Cochran et al. | Induced seismicity strategic vision |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |