CN105629297A - Method for predicting micro fault distribution rules of complex fault-block oilfields - Google Patents
Method for predicting micro fault distribution rules of complex fault-block oilfields Download PDFInfo
- Publication number
- CN105629297A CN105629297A CN201410638665.5A CN201410638665A CN105629297A CN 105629297 A CN105629297 A CN 105629297A CN 201410638665 A CN201410638665 A CN 201410638665A CN 105629297 A CN105629297 A CN 105629297A
- Authority
- CN
- China
- Prior art keywords
- distribution
- fault
- microfault
- stress
- regularity
- 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
Landscapes
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention provides a method for predicting micro fault distribution rules of complex fault-block oilfields. The method for predicting micro fault distribution rules of complex fault-block oilfields comprises following steps: S1. simulating a difference value of a maximum plane primary stress and a minimum plane primary stress, and simulating and predicting minor fault development area through the plane primary stress difference; S2. simulating the distribution of plane shear stress and simulating and predicting the dominant trend of the minor fault through the plane shear stress; S3. simulating the distribution of cross section shear stress, and simulating and predicting the dominant trend of the minor fault through the cross section shear stress; S4. on the basis of above prediction, in combination with theory analysis of fault mechanical causes, establishing an integrated prediction model for micro fault distribution geology. The core of the method for predicting micro fault distribution rules of complex fault-block oilfields is simulation of tectonic stress field based on fault mechanical causes; semi-quantitative prediction of non-well drilling encounter micro fault distribution is realized; the method has directive function to seismic interpretation.
Description
Technical field
The present invention relates to oil field development technical field, especially relate to a kind of method predicting the Complicated Fault Block Oilfield microfault regularity of distribution.
Background technology
In the modification scenario research of Complicated Fault Block Oilfield old liberated area (especially into ultra-high water-containing after date), the research of microfault is the emphasis of meticulous pool description. Microfault refers to the micro-small fault within natural fault blocks, general about the 10m of drop is to less than 10m, development length only has about 100-300m, and exploration phase, initial stage of development profit static distribution are not substantially played control action, but affect the principal element of development late stage remaining oil distribution.
All the time, the regularity of distribution predictive study of microfault has difficulties. In the past in research, it is generally adopted " similar constructions pattern, similar district analogy method " and is predicted. The method is to utilize set up " typical construction pattern " or use similar district, adjacent region to carry out analogy prediction, it is subjective, different researcheres may select different tectonic styles, similar district to carry out analogy, and a basin generally also only has 4-6 kind " tectonic style ", but being used to thousands of blocks of analogy, specific aim is very poor. Therefore, the method is only applicable to the prediction of the forecast of distribution of the bigger tomography of drop, complicated fault system macroscopic law, poor for microfault prediction effect.
For solving microfault regularity of distribution forecasting problem, effectively instruct the seismic interpretation of complicated fault system, improve Complicated Fault Block Oilfield meticulous pool description research precision, carry out remaining oil research technology better, we have invented a kind of method predicting the microfault regularity of distribution, solve the problems referred to above.
Summary of the invention
It is an object of the invention to provide a kind of tectonic stress field stimulation based on the fault mechanics origin cause of formation, it is achieved thereby that the method boring the prediction Complicated Fault Block Oilfield microfault regularity of distribution of the sxemiquantitative prediction meeting microfault distribution without well.
The purpose of the present invention can be achieved by the following technical measures: the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution, the method of this prediction Complicated Fault Block Oilfield microfault regularity of distribution includes: step 1, the difference of simulation plane minimax principal stress, by plane deviator stress simulation and forecast abundant little faults district; Step 2, the distribution of simulation plane shear stress, moved towards by plane shear stress simulation and forecast craven fault advantage; Step 3, the distribution of simulated section shear stress, cut by section and answer simulation and forecast craven fault advantage to be inclined to; And step 4, on the basis based on above-mentioned prediction, in conjunction with the theory analysis of the fault mechanics origin cause of formation, set up microfault distribution geological syntheses forecast model.
The purpose of the present invention realizes also by following technical measures:
The method of this prediction Complicated Fault Block Oilfield microfault regularity of distribution also includes, before step 1, study two, three grades of major faults and namely first deposit tomography, and these mechanics parameters of Poisson's ratio, elastic modelling quantity are determined in analysis by experiment, for carrying out structure stress scene simulation method research, it was predicted that the characteristic parameter that microfault is grown is layed foundation.
In step 1, setting up that plane is maximum, minimum principal stress difference cloth simulation drawing, the Spring layer of the minimax deviator stress in figure is the favourable development area of microfault.
In step 2, setting up plane shearing stress distribution simulation drawing, Tu Zhong negative value district represents dextrorotation shear stress, tomography advantage trend for south east, northwest to; Representing left-handed shear stress on the occasion of district, tomography advantage trend is northwest (NW) east southeast direction.
In step 3, setting up work area section shearing stress distribution simulation drawing, the tomography advantage tendency in negative value district is inclined for south, and the tomography advantage tendency on the occasion of district is inclined for north.
In step 4, work area microfault distribution geological syntheses forecast model is set up, including Fault density, tomography advantage trend, advantage tendency and these predictive contents of mature fault pattern, it is achieved the prediction to the microfault regularity of distribution.
The method of the prediction Complicated Fault Block Oilfield microfault regularity of distribution in the present invention, solve a difficult problem for microfault forecast of distribution in the modification scenario research of Complicated Fault Block Oilfield old liberated area, it is primarily directed to Complicated Fault Block Oilfield old liberated area and improves in recovery ratio research, to drop��10m's, microfault within natural fault blocks carries out geological analysis, predict method " geological syntheses model " predicted method of its regularity of distribution, its core is based on the tectonic stress field stimulation of the fault mechanics origin cause of formation, it is achieved thereby that bore the sxemiquantitative prediction meeting microfault distribution without well, seismic interpretation is had good directive function. the method is on the basis that research two, three grades of work area major fault (first depositing tomography) and the mechanics parameter experimental analysis such as Poisson's ratio, elastic modelling quantity are determined, carry out structure stress scene simulation method research, the characteristic parameter that prediction microfault is grown: by plane deviator stress simulation and forecast abundant little faults district, moved towards by plane shear stress simulation and forecast craven fault advantage, be inclined to by section stress field simulation predicting small scale faults advantage. on the basis of three above key characterization parameter Accurate Prediction, in conjunction with the theory analysis of the fault mechanics origin cause of formation, set up the geological syntheses forecast model in an actual work area, the microfault regularity of distribution is predicted, instructs seismic interpretation.
Accompanying drawing explanation
Fig. 1 is the flow chart of a specific embodiment of the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution of the present invention;
Fig. 2 is that work area plane is maximum, minimum principal stress difference cloth simulation drawing;
Fig. 3 is work area plane shearing stress distribution simulation drawing;
Fig. 4 is work area section shearing stress distribution simulation drawing;
Fig. 5 is work area microfault distribution geological syntheses forecast model.
Detailed description of the invention
For making the above and other purpose of the present invention, feature and advantage to become apparent, cited below particularly go out preferred embodiment, and coordinate institute's accompanying drawings, be described in detail below.
As it is shown in figure 1, the flow chart of the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution that Fig. 1 is the present invention.
In step 101, two, three grades of work area of research major fault (first depositing tomography), and the mechanics parameter such as Poisson's ratio, elastic modelling quantity is determined in analysis by experiment, for carrying out structure stress scene simulation method research, it was predicted that the characteristic parameter that microfault is grown is layed foundation. Flow process enters into step 102.
In step 102, first simulate the difference of plane minimax principal stress, by plane deviator stress simulation and forecast abundant little faults district. Fig. 2 is that work area plane is maximum, minimum principal stress difference cloth simulation drawing, and the Spring layer of the minimax deviator stress in figure is the favourable development area of microfault. Flow process enters into step 103.
In step 103, secondly simulate the distribution of plane shear stress, moved towards by plane shear stress simulation and forecast craven fault advantage. Fig. 3 is work area plane shearing stress distribution simulation drawing, and Tu Zhong negative value district represents dextrorotation shear stress, tomography advantage trend for south east, northwest to; Represent left-handed shear stress on the occasion of district, tomography advantage trend for south east, northwest to. Flow process enters into step 104.
In step 104, the distribution of simulated section shear stress again, it is inclined to by section stress field simulation predicting small scale faults advantage. Fig. 4 is work area section shearing stress distribution simulation drawing, the same previous step of meaning, and the tomography advantage tendency in negative value district is inclined for south, and the tomography advantage tendency on the occasion of district is inclined for north. Flow process enters into step 105.
In step 105, finally, on the basis that above three microfaults distribution key characterization parameter (favourable development area, advantage trend, advantage tendency) is predicted, in conjunction with the theory analysis of the fault mechanics origin cause of formation, geological syntheses model is set up. Fig. 5 is work area microfault distribution geological syntheses forecast model, which includes the predictive contents such as Fault density, tomography advantage trend, advantage tendency and mature fault pattern, thus realizing the prediction to the microfault regularity of distribution, can be used for instructing seismic interpretation.
Claims (6)
1. the method predicting the Complicated Fault Block Oilfield microfault regularity of distribution, it is characterised in that the method for this prediction Complicated Fault Block Oilfield microfault regularity of distribution includes:
Step 1, the difference of simulation plane minimax principal stress, by plane deviator stress simulation and forecast abundant little faults district;
Step 2, the distribution of simulation plane shear stress, moved towards by plane shear stress simulation and forecast craven fault advantage;
Step 3, the distribution of simulated section shear stress, cut by section and answer simulation and forecast craven fault advantage to be inclined to; And
Step 4, on the basis based on above-mentioned prediction, in conjunction with the theory analysis of the fault mechanics origin cause of formation, sets up microfault distribution geological syntheses forecast model.
2. the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution according to claim 1, it is characterized in that, the method of this prediction Complicated Fault Block Oilfield microfault regularity of distribution also includes, before step 1, study two, three grades of major faults and namely first deposit tomography, and these mechanics parameters of Poisson's ratio, elastic modelling quantity are determined in analysis by experiment, for carrying out structure stress scene simulation method research, it was predicted that the characteristic parameter that microfault is grown is layed foundation.
3. the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution according to claim 1, it is characterized in that, in step 1, setting up that plane is maximum, minimum principal stress difference cloth simulation drawing, the Spring layer of the minimax deviator stress in figure is the favourable development area of microfault.
4. the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution according to claim 1, it is characterised in that in step 2, setting up plane shearing stress distribution simulation drawing, Tu Zhong negative value district represents dextrorotation shear stress, tomography advantage trend for south east, northwest to; Representing left-handed shear stress on the occasion of district, tomography advantage trend is northwest (NW) east southeast direction.
5. the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution according to claim 1, it is characterized in that, in step 3, set up work area section shearing stress distribution simulation drawing, the tomography advantage tendency in negative value district is inclined for south, and the tomography advantage tendency on the occasion of district is inclined for north.
6. the method for the prediction Complicated Fault Block Oilfield microfault regularity of distribution according to claim 1, it is characterized in that, in step 4, set up work area microfault distribution geological syntheses forecast model, including Fault density, tomography advantage trend, advantage tendency and these predictive contents of mature fault pattern, it is achieved the prediction to the microfault regularity of distribution.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410638665.5A CN105629297A (en) | 2014-11-07 | 2014-11-07 | Method for predicting micro fault distribution rules of complex fault-block oilfields |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410638665.5A CN105629297A (en) | 2014-11-07 | 2014-11-07 | Method for predicting micro fault distribution rules of complex fault-block oilfields |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105629297A true CN105629297A (en) | 2016-06-01 |
Family
ID=56044409
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410638665.5A Pending CN105629297A (en) | 2014-11-07 | 2014-11-07 | Method for predicting micro fault distribution rules of complex fault-block oilfields |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105629297A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106526675A (en) * | 2016-12-28 | 2017-03-22 | 中国石油化工股份有限公司 | Automatic extraction method for fault space parameter |
| CN107703542A (en) * | 2017-08-31 | 2018-02-16 | 中国石油天然气集团公司 | A kind of determination method and apparatus of seismic horizon |
| CN108680952A (en) * | 2018-04-03 | 2018-10-19 | 刘敬寿 | A kind of strike-slip fault structural evolution analytic method |
| CN111474583A (en) * | 2020-06-03 | 2020-07-31 | 中国石油化工股份有限公司 | Fault interpretation method and structural trap identification method for fault block oil reservoir |
| CN112576246A (en) * | 2020-12-11 | 2021-03-30 | 中国海洋石油集团有限公司 | Method for predicting low-order fault in offshore complex fault block oil field |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7414919B2 (en) * | 2004-06-25 | 2008-08-19 | Petrochina Co., Ltd. | Method for improving the seismic resolution |
| CN102654586A (en) * | 2012-05-18 | 2012-09-05 | 北京师范大学 | Multi-scale fracture modeling method |
| CN103245971A (en) * | 2013-04-25 | 2013-08-14 | 中国石油天然气股份有限公司 | Well break point guided seismic minor fault interpretation method and device |
| CN103838936A (en) * | 2014-03-25 | 2014-06-04 | 中国石油大学(华东) | High-precision tectonic stress field simulation method applicable to turbidite sand low-permeability reservoirs |
-
2014
- 2014-11-07 CN CN201410638665.5A patent/CN105629297A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7414919B2 (en) * | 2004-06-25 | 2008-08-19 | Petrochina Co., Ltd. | Method for improving the seismic resolution |
| CN102654586A (en) * | 2012-05-18 | 2012-09-05 | 北京师范大学 | Multi-scale fracture modeling method |
| CN103245971A (en) * | 2013-04-25 | 2013-08-14 | 中国石油天然气股份有限公司 | Well break point guided seismic minor fault interpretation method and device |
| CN103838936A (en) * | 2014-03-25 | 2014-06-04 | 中国石油大学(华东) | High-precision tectonic stress field simulation method applicable to turbidite sand low-permeability reservoirs |
Non-Patent Citations (3)
| Title |
|---|
| 付晓龙 等: "汊涧斜坡带阜宁期应力场数值模拟及低级序断层发育规律预测", 《地质力学学报》 * |
| 刘显太 等: "低序级断层识别与精细描述技术研究", 《特种油气藏》 * |
| 戴俊生 等: "基于应力场模拟解释河西务构造带孔店__沙四期断层特征", 《天然气地球科学》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106526675A (en) * | 2016-12-28 | 2017-03-22 | 中国石油化工股份有限公司 | Automatic extraction method for fault space parameter |
| CN107703542A (en) * | 2017-08-31 | 2018-02-16 | 中国石油天然气集团公司 | A kind of determination method and apparatus of seismic horizon |
| CN108680952A (en) * | 2018-04-03 | 2018-10-19 | 刘敬寿 | A kind of strike-slip fault structural evolution analytic method |
| CN111474583A (en) * | 2020-06-03 | 2020-07-31 | 中国石油化工股份有限公司 | Fault interpretation method and structural trap identification method for fault block oil reservoir |
| CN112576246A (en) * | 2020-12-11 | 2021-03-30 | 中国海洋石油集团有限公司 | Method for predicting low-order fault in offshore complex fault block oil field |
| CN112576246B (en) * | 2020-12-11 | 2023-10-31 | 中国海洋石油集团有限公司 | Prediction method for low-order fault in offshore complex fault block oil field |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sun et al. | Investigating the effect of improved fracture conductivity on production performance of hydraulically fractured wells: Field-case studies and numerical simulations | |
| Yu et al. | An efficient reservoir-simulation approach to design and optimize unconventional gas production | |
| CN105629297A (en) | Method for predicting micro fault distribution rules of complex fault-block oilfields | |
| Bourne et al. | Predictive modelling of naturally fractured reservoirs using geomechanics and flow simulation | |
| Kalantari-Dahaghi et al. | Numerical simulation and multiple realizations for sensitivity study of shale gas reservoir | |
| CN104500050A (en) | Fractured reservoir permeability tensor and anisotropy quantitative prediction method | |
| Aimene et al. | Modeling multiple hydraulic fractures interacting with natural fractures using the material point method | |
| Luo et al. | The use of rate-transient-analysis modeling to quantify uncertainties in commingled tight gas production-forecasting and decline-analysis parameters in the Alberta deep basin | |
| Quinao et al. | Applications of experimental design and response surface method in probabilistic geothermal resource assessment–preliminary results | |
| Yu et al. | Embedded discrete fracture model assisted study of gas transport mechanisms and drainage area for fractured shale gas reservoirs | |
| Gu et al. | A method for evaluation of water flooding performance in fractured reservoirs | |
| Zhang et al. | Uncertainty Analysis and Assisted History Matching Workflow in Shale Oil Reservoirs | |
| Ali et al. | A semi-analytical method for history matching and improving geological models of layered reservoirs: CGM analytical method | |
| CN114862609A (en) | Oil reservoir exploitation method for ultra-high water-cut oil field | |
| Min et al. | Application of decision aids for tunneling (DAT) to a drill & blast tunnel | |
| Aarnes et al. | Evergreen workflows that capture uncertainty–the benefits of an unlocked structure | |
| Saputelli et al. | Waterflood recovery optimization using intelligent wells and decision analysis | |
| CN113887067A (en) | Compact low-permeability reservoir fracturing well pattern gas flooding effect prediction method based on LSTM | |
| Luo et al. | Optimizing the drilled well patterns for CBM recovery via numerical simulations and data envelopment analysis | |
| Sifuentes et al. | Samarang Integrated Operations (IO): Integrated Asset Modeling-An Innovative Approach For Long Term Production Planning Focused On Enhance Oil Recovery | |
| CN114881383A (en) | Novel method for calculating layered recoverable reserves of commingled production well | |
| Ibrahim et al. | A Novel Approach Linking Structural Restoration and Multiphase Fluid-Flow Modeling Using 3D Geomechanics in a North Kuwait Giant Carbonate Reservoir | |
| Sambo et al. | An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir | |
| Al-Qahtani et al. | Complex well modeling workflow enabling full field optimization and forward decisions | |
| Rezaei et al. | Applications of Machine Learning for Estimating the Stimulated Reservoir Volume (SRV) |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20160601 |
|
| WD01 | Invention patent application deemed withdrawn after publication |