CN102621594A - Bedding structure recognition method and system - Google Patents
Bedding structure recognition method and system Download PDFInfo
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- CN102621594A CN102621594A CN2012100952439A CN201210095243A CN102621594A CN 102621594 A CN102621594 A CN 102621594A CN 2012100952439 A CN2012100952439 A CN 2012100952439A CN 201210095243 A CN201210095243 A CN 201210095243A CN 102621594 A CN102621594 A CN 102621594A
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Abstract
The invention discloses bedding structure recognition method and system, which overcome the defects that the traditional bedding structure recognition technology is single and has low reliability. The method comprises the following steps of: obtaining the lamina form combinations of outcrop or core data and the relationship between the lamina and the bed series interface to determine the bedding structure type; obtaining line form combinations in an imaging data image corresponding to the outcrop or core data, and determining the line form combination characteristics of different bedding structure types in the imaging data image; obtaining the inclination angle vector mode reflected by inclination angles and inclination degrees in the inclination degree data corresponding to the outcrop or core data, and determining the inclination degree vector characteristics of different bedding structure types; determining the bedding structure mode according to the line form combination characteristics and the inclination degree vector characteristics of different bedding structure types in the imaging data image by combining the formation cause mechanism of bedding deposition and the lithological type. The invention can provide a basis for the application of imaging and well logging technique and the like.
Description
Technical field
The present invention relates to the recognition technology of bedding structure, relate in particular to a kind of bedding structure recognition methods and system.
Background technology
The stratification structure that bedding forms in layer when being the sediment deposition, the key element of forming bedding comprises lamina and series of strata.At present, bedding structure be identified on the geology mainly be according to appear or the rock core material object in phenomenon observe identification, in well logging, then mainly be to discern according to imaging logging image pattern or dipmeter logging arrow pattern.
The recognition methods of constructing in these two kinds of layers at present all has certain limitation.For down-hole formation, just be difficult to obtain deposition bedding structure when lacking rock core, even there is rock core also can't carry out orientation to rock core.Adopt well-log information identification bedding structure, because lacking of lamination geology pattern is proved, its result's accuracy is just very limited again.
Summary of the invention
Technical matters to be solved by this invention is the defective that recognition technology is single and reliability is lower that overcomes present bedding structure.
In order to solve the problems of the technologies described above, the invention provides the recognition methods of a kind of bedding structure, comprising:
Acquisition is appeared or the lamina form families of rock core information and the relation at lamina and series of strata interface are confirmed the bedding structural type;
Acquisition appear or the corresponding imaging source map of rock core information picture in the line strip state combination, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture;
Acquisition appear or the corresponding dip information of rock core information in the dip vector pattern that reflected of inclination angle and tendency size, confirm the dip vector characteristic of different bedding structural types;
According to line strip state combination characteristic, the dip vector characteristic of different bedding structural types in imaging source map picture,, confirm the bedding structural model in conjunction with the origin cause of formation mechanism and the lithology type of bedding deposition.
Wherein, different bedding structural models have reflected the difference of sedimental color, granularity, composition and lithology.
Wherein, the bedding structural model comprises:
Horizontal stratification, wavy bedding, incision template shape diagonal stratification, cut template shape diagonal stratification, trough cross-stratification, block bedding and pinniform diagonal stratification down.
The present invention also provides a kind of bedding structure recognition system, comprising:
The type determination module, be used to obtain to appear the perhaps lamina form families of rock core information and the relation at lamina and series of strata interface are confirmed the bedding structural type;
Line strip state combination characteristic determination module; Link to each other with the type determination module; Be used for obtaining to appear or the line strip state combination of the corresponding imaging source map of rock core information picture, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture;
Dip vector characteristic determination module links to each other with the type determination module, is used for obtaining to appear or rock core information corresponding dip information inclination angle and the big or small dip vector pattern that is reflected of tendency, confirms the dip vector characteristic of different bedding structural types;
The pattern determination module; Link to each other with line strip state combination characteristic determination module and dip vector characteristic determination module; Be used for according to line strip state combination characteristic, the dip vector characteristic of different bedding structural types at imaging source map picture; In conjunction with the origin cause of formation mechanism and the lithology type of bedding deposition, confirm the bedding structural model.
Wherein, the definite different bedding structural models of pattern determination module have reflected the difference of sedimental color, granularity, composition and lithology.
Wherein, the bedding structural model confirmed of pattern determination module comprises horizontal stratification, wavy bedding, incision template shape diagonal stratification, cuts template shape diagonal stratification, trough cross-stratification, block bedding and pinniform diagonal stratification down.
Compared with prior art; Embodiments of the invention combine well-log information and geological theory; Set up the comprehensive model of cognition of common bedding structure, can to analysis, the analysis of thing source and SEDIMENTARY FACIES ANALYSIS etc. foundation be provided for the application of imaging logging techniques, the paleocurrent of clastic reservoir rock.
Other features and advantages of the present invention will be set forth in instructions subsequently, and, partly from instructions, become obvious, perhaps understand through embodiment of the present invention.The object of the invention can be realized through the structure that in instructions, claims and accompanying drawing, is particularly pointed out and obtained with other advantages.
Description of drawings
Fig. 1 is the schematic flow sheet of embodiment of the invention bedding structure recognition methods.
Fig. 2 is the determined 7 kinds of bedding structural models of embodiment of the invention bedding structure recognition methods.
Fig. 3 is the structural representation of embodiment of the invention bedding structure recognition system.
Embodiment
For making the object of the invention, technical scheme and advantage clearer, hereinafter will combine accompanying drawing that embodiments of the invention are elaborated.Need to prove that under the situation of not conflicting, embodiment among the application and the characteristic among the embodiment be combination in any each other.
Offshore oilfield drilling cost height is cored less, and the deposition bedding tectonic information on stratum can't obtain.And deposition bedding structure is one of core content of sedimentology research, and is especially significant in SEDIMENTARY FACIES ANALYSIS, and thing source direction in the time of can indicating the sand body deposition and paleocurrent are to information.Embodiments of the invention combine well-log information and geological theory etc., set up the comprehensive model of cognition of common bedding structure, for SEDIMENTARY FACIES ANALYSIS provides foundation.
As shown in Figure 1, the bedding structure recognition methods of the embodiment of the invention mainly comprises the steps:
Step S110 obtains to appear or the lamina form families of rock core information and the relation at lamina and series of strata interface, the perhaps bedding structural type of rock core information of confirming to appear;
Step S120, obtain to appear or the corresponding imaging source map of rock core information picture in the line strip state combination, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture.
Step S130, obtain to appear or the corresponding dip information of rock core information in the dip vector pattern that reflected of inclination angle and tendency size, confirm the dip vector characteristic of different bedding structural types.
Step S140 according to line strip state combination characteristic, the dip vector characteristic of different bedding structural types in imaging source map picture, in conjunction with the origin cause of formation mechanism and the lithology type of bedding deposition, confirms the bedding structural model.
7 kinds of bedding structural models that the embodiment of the invention relates to; Belong to flow into because of sedimentary structure; Different hydrodynamic force energy conditions forms different bedding structures; And show by the vertical variation in edges such as sedimental color, granularity, composition and lithology, therefore, can confirm the origin cause of formation mechanism and the type of different beddings according to sedimentary environment and corresponding hydrodynamic condition thereof.
Fig. 2 has provided the signal of determined 7 kinds of bedding structural models in the embodiment of the invention.In Fig. 2, the N under the imaging pattern represents north, and E represents east, and S represents south, and W represents the west; 0-90 under the pattern of inclination angle represents the inclination angle angle.
Horizontal stratification (Hb) shows as one group of one group horizontal line substantially parallel with aspect on imaging source map picture, on arrow plot, show as green pattern (one group of inclination angle equal and opposite in direction, the dip vector that tendency is consistent).
Wavy bedding (Wb) shows as one group of substantially parallel with aspect generally lines on imaging source map picture, the amplitude difference is little, but the orientation is changeful.It is less on arrow plot, to show as the angle variation, and the orientation comes and go.
Incision template shape diagonal stratification (Pc) shows as sinusoidal curve on imaging source map picture, general top lamina occurrence is basic identical, and the bottom occurrence slows down gradually, and lamina shows that the bottom is tangent, the top is cut mutually in the series of strata.On arrow plot, showing as top is green pattern, and the bottom is blue pattern (one group of inclination angle diminishes gradually, the dip vector that tendency is consistent) combination.
Under cut template shape diagonal stratification (Ps) on imaging source map picture, to show as the sinusoidal curve occurrence basic identical, lamina shows that the end, top cut off in the series of strata, the angle of inclination is consistent.On arrow plot, show as green pattern.
Trough cross-stratification (Tc) is that the series of strata group that the sinusoidal curve of cover different angles shows constitutes on imaging source map picture; It between two series of strata interfaces the lamina that cuts off of arc; The sinusoidal curve occurrence difference of different series of strata groups is bigger, and last group of sinusoidal curve degraded for one group by the back.On arrow plot, show as little red pattern (one group of inclination angle becomes greatly gradually, the dip vector that tendency is consistent), blue pattern combination that one group short mode line connects.
Block bedding (Mb) sinusoidal curve on imaging data image slices does not have rule or can't see sinusoidal curve, on arrow plot, shows as mixed and disorderly or blank pattern.
Pinniform diagonal stratification (Fc) shows as the occurrence of two adjacent groups lamina series of strata sinusoidal curve on imaging source map picture opposite, on arrow plot, shows as two prescriptions to opposite dip vector blue pattern.
As shown in Figure 3, the bedding structure recognition system of the embodiment of the invention mainly comprises type determination module 310, line strip state combination characteristic determination module 320, dip vector characteristic determination module 330 and pattern determination module 340.
Line strip state combination characteristic determination module 320; Link to each other with type determination module 310; Be used for obtaining to appear or the line strip state combination of the corresponding imaging source map of rock core information picture, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture.
Dip vector characteristic determination module 330 links to each other with type determination module 310, is used for obtaining to appear or rock core information corresponding dip information inclination angle and the big or small dip vector pattern that is reflected of tendency, confirms the dip vector characteristic of different bedding structural types.
Wherein, pattern determination module 340 definite different bedding structural models have reflected the difference of sedimental color, granularity, composition and lithology.
Wherein, the bedding structural models confirmed of pattern determination module 340 comprise horizontal stratification as shown in Figure 2, wavy bedding, incision template shape diagonal stratification, cut template shape diagonal stratification, trough cross-stratification, block bedding and pinniform diagonal stratification down.
The bedding of the embodiment of the invention is constructed comprehensive recognition technology by rock core scale imaging data; According to different shape lines array mode in the imaging source map picture; In conjunction with the dip vector pattern; Fully merge imaging logging image morphological feature, dipmeter logging arrow pattern and bedding sedimentary origin mechanism, realized the unification of three kinds of technical methods.Embodiments of the invention have merged the image line bar form families characteristic of imaging logging, the arrow pattern characteristic of dipmeter logging and the geologic model that bedding forms; The three-dimensional integrated bedding structure recognition technology of being set up has comprised common bedding structural type, and the by force credible and kind of identification achievement is comparatively complete.
Utilize embodiments of the invention, can be through Image Logging Data and the lamina form families that dip information provided and the response characteristic of dip vector, compare with bedding tectonic geology pattern in the embodiment of the invention, thereby confirm and judge the type of bedding structure.
Embodiments of the invention can play a significant role aspect the GEOLOGICAL APPLICATION of expanding well-log information; Can to analysis, the analysis of thing source and SEDIMENTARY FACIES ANALYSIS etc. important evidence be provided for the paleocurrent of clastic reservoir rock; Can be used for estimating and studying many complicated reservoirs, can satisfy the needs of oil field SEDIMENTARY FACIES ANALYSIS.
Though the embodiment that the present invention disclosed as above, the embodiment that described content just adopts for the ease of understanding the present invention is not in order to limit the present invention.Technician under any the present invention in the technical field; Under the prerequisite of spirit that does not break away from the present invention and disclosed and scope; Can do any modification and variation what implement in form and on the details; But scope of patent protection of the present invention still must be as the criterion with the scope that appending claims was defined.
Claims (6)
1. bedding structure recognition methods comprises:
Acquisition is appeared or the lamina form families of rock core information and the relation at lamina and series of strata interface are confirmed the bedding structural type;
Acquisition appear or the corresponding imaging source map of rock core information picture in the line strip state combination, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture;
Acquisition appear or the corresponding dip information of rock core information in the dip vector pattern that reflected of inclination angle and tendency size, confirm the dip vector characteristic of different bedding structural types;
According to line strip state combination characteristic, the dip vector characteristic of different bedding structural types in imaging source map picture,, confirm the bedding structural model in conjunction with the origin cause of formation mechanism and the lithology type of bedding deposition.
2. method according to claim 1, wherein:
Different bedding structural models have reflected the difference of sedimental color, granularity, composition and lithology.
3. method according to claim 1, wherein, the bedding structural model comprises:
Horizontal stratification, wavy bedding, incision template shape diagonal stratification, cut template shape diagonal stratification, trough cross-stratification, block bedding and pinniform diagonal stratification down.
4. a bedding is constructed recognition system, comprising:
The type determination module, be used to obtain to appear the perhaps lamina form families of rock core information and the relation at lamina and series of strata interface are confirmed the bedding structural type;
Line strip state combination characteristic determination module; Link to each other with the type determination module; Be used for obtaining to appear or the line strip state combination of the corresponding imaging source map of rock core information picture, confirm the line strip state combination characteristic of different bedding structural types in imaging source map picture;
Dip vector characteristic determination module links to each other with the type determination module, is used for obtaining to appear or rock core information corresponding dip information inclination angle and the big or small dip vector pattern that is reflected of tendency, confirms the dip vector characteristic of different bedding structural types;
The pattern determination module; Link to each other with line strip state combination characteristic determination module and dip vector characteristic determination module; Be used for according to line strip state combination characteristic, the dip vector characteristic of different bedding structural types at imaging source map picture; In conjunction with the origin cause of formation mechanism and the lithology type of bedding deposition, confirm the bedding structural model.
5. system according to claim 4, wherein:
The different bedding structural models that the pattern determination module is confirmed have reflected the difference of sedimental color, granularity, composition and lithology.
6. system according to claim 4, wherein:
The bedding structural model that the pattern determination module is confirmed comprises horizontal stratification, wavy bedding, incision template shape diagonal stratification, cuts template shape diagonal stratification, trough cross-stratification, block bedding and pinniform diagonal stratification down.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104142523A (en) * | 2014-07-23 | 2014-11-12 | 中国地质大学（北京） | Representation method for rich organic matter mud rock sedimentary structure |
| CN104914482A (en) * | 2014-03-13 | 2015-09-16 | 中国石油化工股份有限公司 | Method of quantitatively identifying complex glutenite lithofacies association types |
| CN108956941A (en) * | 2018-06-12 | 2018-12-07 | 中国石油天然气股份有限公司 | Shale stratification recognition methods |
| CN112253087A (en) * | 2020-10-20 | 2021-01-22 | 河南理工大学 | Biological disturbance reservoir physical property calculation method based on multi-source logging data |
| CN114359569A (en) * | 2022-03-09 | 2022-04-15 | 中国科学院地质与地球物理研究所 | Rock bedding recognition method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1049915A (en) * | 1989-06-29 | 1991-03-13 | 切夫伦研究技术公司 | The response of tidal force is analyzed the method for hydrocarbon reservoir by measuring hydrocarbon reservoir |
| JP2008107252A (en) * | 2006-10-26 | 2008-05-08 | Chugoku Electric Power Co Inc:The | Geologic structure evaluation method and device |
| JP4509865B2 (en) * | 2005-06-02 | 2010-07-21 | 東京電力株式会社 | Layer structure estimation method and analysis apparatus for analyzing layer structure |
| CN102203638A (en) * | 2008-09-19 | 2011-09-28 | 雪佛龙美国公司 | Computer-implemented systems and methods for use in modeling a geomechanical reservoir system |
-
2012
- 2012-03-31 CN CN201210095243.9A patent/CN102621594B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1049915A (en) * | 1989-06-29 | 1991-03-13 | 切夫伦研究技术公司 | The response of tidal force is analyzed the method for hydrocarbon reservoir by measuring hydrocarbon reservoir |
| JP4509865B2 (en) * | 2005-06-02 | 2010-07-21 | 東京電力株式会社 | Layer structure estimation method and analysis apparatus for analyzing layer structure |
| JP2008107252A (en) * | 2006-10-26 | 2008-05-08 | Chugoku Electric Power Co Inc:The | Geologic structure evaluation method and device |
| CN102203638A (en) * | 2008-09-19 | 2011-09-28 | 雪佛龙美国公司 | Computer-implemented systems and methods for use in modeling a geomechanical reservoir system |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104914482A (en) * | 2014-03-13 | 2015-09-16 | 中国石油化工股份有限公司 | Method of quantitatively identifying complex glutenite lithofacies association types |
| CN104142523A (en) * | 2014-07-23 | 2014-11-12 | 中国地质大学（北京） | Representation method for rich organic matter mud rock sedimentary structure |
| CN104142523B (en) * | 2014-07-23 | 2017-01-11 | 中国地质大学（北京） | Representation method for rich organic matter mud rock sedimentary structure |
| CN108956941A (en) * | 2018-06-12 | 2018-12-07 | 中国石油天然气股份有限公司 | Shale stratification recognition methods |
| CN112253087A (en) * | 2020-10-20 | 2021-01-22 | 河南理工大学 | Biological disturbance reservoir physical property calculation method based on multi-source logging data |
| CN114359569A (en) * | 2022-03-09 | 2022-04-15 | 中国科学院地质与地球物理研究所 | Rock bedding recognition method, device, equipment and storage medium |
| US11436738B1 (en) | 2022-03-09 | 2022-09-06 | Institute Of Geology And Geophysics, Chinese Academy Of Sciences | Rock stratification identification method and apparatus, device and storage medium |
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Address after: 100010 Chaoyangmen North Street, Dongcheng District, Dongcheng District, Beijing Co-patentee after: China Oilfield Services Limited Patentee after: China Offshore Oil Group Co., Ltd. Address before: 100010 Chaoyangmen North Street, Dongcheng District, Dongcheng District, Beijing Co-patentee before: China Oilfield Services Limited Patentee before: China National Offshore Oil Corporation |
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