CN101980055A - Digital modeling method for seismic exploration - Google Patents
Digital modeling method for seismic exploration Download PDFInfo
- Publication number
- CN101980055A CN101980055A CN 201010565905 CN201010565905A CN101980055A CN 101980055 A CN101980055 A CN 101980055A CN 201010565905 CN201010565905 CN 201010565905 CN 201010565905 A CN201010565905 A CN 201010565905A CN 101980055 A CN101980055 A CN 101980055A
- Authority
- CN
- China
- Prior art keywords
- point
- gray
- papery
- starting point
- isoline
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 24
- IYLGZMTXKJYONK-ACLXAEORSA-N (12s,15r)-15-hydroxy-11,16-dioxo-15,20-dihydrosenecionan-12-yl acetate Chemical compound O1C(=O)[C@](CC)(O)C[C@@H](C)[C@](C)(OC(C)=O)C(=O)OCC2=CCN3[C@H]2[C@H]1CC3 IYLGZMTXKJYONK-ACLXAEORSA-N 0.000 claims description 18
- IYLGZMTXKJYONK-UHFFFAOYSA-N ruwenine Natural products O1C(=O)C(CC)(O)CC(C)C(C)(OC(C)=O)C(=O)OCC2=CCN3C2C1CC3 IYLGZMTXKJYONK-UHFFFAOYSA-N 0.000 claims description 18
- 241001270131 Agaricus moelleri Species 0.000 claims description 5
- 230000004075 alteration Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 4
- 239000003208 petroleum Substances 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 abstract 3
- 238000013528 artificial neural network Methods 0.000 description 9
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000013529 biological neural network Methods 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 210000000567 greater sac Anatomy 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Landscapes
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention discloses a digital modeling method for seismic exploration, which relates to the technical field of processing and explanation of petroleum seismic exploration data, aims at the fact that the picture quality of a paper structure diagram is good, the continuity of contour lines in the paper structure diagram on the picture is good, and processes the paper structure diagram by adopting an automatic tracking algorithm one by one.
Description
Technical field
The present invention relates to oil seismic exploration Data Processing and interpretation technique field, exactly relate to a kind of modeling method that the relief surface elastic wave is just being drilled that is applied to.
Background technology
Along with the high speed development of China's economic, also increasing to the demand of petroleum-based energy, national correlation department has strengthened the dynamics and the range of petroleum prospecting; Along with to the carrying out of mountain region seismic survey work with complicated earth surface structure,, also more and more higher to the accuracy requirement of geologic model in order to carry out the mountain region seismic prospecting more accurately, more targetedly.Therefore, how to provide the forward model that reacts the underground medium situation more really to become geophysics worker's vital task.By digitizing, then can obtain more truly to reflect the geologic model of subsurface picture, for the geophysics forward simulation provides technical support to the papery structrual contour.
Nearly ten years high speed developments along with computer hardware and software, our tectonic structure isogram is stored in the computer hardware with electronic format mostly at present, but with the geologic information that we geologist of previous decades gathers all is to store with the form of papery, and papery tectonic structure isogram is preserved and utilized has become our urgent problem.How to utilize again and spend the valuable material that a large amount of manpower and materials collect before us for many years and become current geophysics and important topic of geology subject.
The papery structural contour map scanning picture that the main target of papery structural contour map digitizing function just is based on different gray scales carries out the precise and high efficiency of isoline and follows the trail of automatically, to realize the digitizing of papery structural contour map, for seismic prospecting provides a kind of new modeling method, farthest excavate the practical value of historical summary simultaneously.The digitized difficult point of papery structural map is a problem of image recognition, and it belongs to the category of computer graphics, mainly contains following several disposal route at the computer graphics subject at this problem at present:
1, profile method of identification
At present for the general useful broken line segmentation of the extraction algorithm of profile more accurately of bianry image and to sectional curve match, polygonal approximation approach, method such as piecewise linear approximation, they all exist calculated amount big, the problem that arithmetic speed is slow.They can't be used in as inline graphics and discern under the application scenario that this class has relatively high expectations to real-time.Figure makes it generate a bianry image matrix (wherein visuals is entirely for white, and background parts for the ease of analyzing, all uses 1 to represent each point of visuals for black, and background dot is represented with 0) after being scanned into computing machine.Usually scanning is advanced the image of computing machine, pattern edge all can some little sawtooth, and the inner general cavity of not having, and also can not produce the edge noise of strip.
2, based on the neural network image recognition methods
Image recognition relates to a large amount of information computings, requires that processing speed is fast, accuracy of identification is high, and the real-time of neural network and fault-tolerance will meet the requirement of image recognition.Utilize improved BP neural network algorithm the rotational distortion image is located and to discern, improve algorithm the additional momentum item is combined with adaptive learning speed, suppressed network effectively and be absorbed in local minimum point, improved the training speed of network.
3, Hopfield network image recognition methods
1982, Hopfield proposed a kind of Feedback Neural Network model (HNN) [3-4], and the neural network of proof under high strength the connects synergy of depending on the collective can spontaneous generation be calculated behavior.By the successful solution of TSP problem, thereby open up neural network model newly turning up the soil in computer science is used, and be subjected to extensive concern and application.The Hopfield network had once been opened up new research approach for the development process of artificial neural network as a kind of neural network of full continuous type.It utilizes and different architectural feature and the learning methods of stratum's type neural network, and the memory mechanism of simulation biological neural network has obtained gratifying result.Although the Hopfield neural network is just to the rough of brain and simple imitation, no matter on function, on scale, all there has been bigger gap than real neural network.
Summary of the invention
For solving the problems of the technologies described above, the present invention proposes a kind of modeling method that the relief surface elastic wave is just being drilled that is applied to, the present invention is based on the papery structural contour map scanning picture of different gray scales, according to papery structural contour map picture quality and the successional difference of isoline, realized the automatic tracking of papery structural contour map precise and high efficiency, automatically follow the trail of the digitizing that has realized the papery structural contour map after finishing, for seismic prospecting provides a kind of new modeling method.
The present invention realizes by adopting following technical proposals:
A kind of digital modeling method that is used for seismic prospecting, it is characterized in that: the picture quality at the papery structural map is relatively good, and the continuity on picture of the isoline in the papery structural map is also relatively good, adopts automatic one by one tracing algorithm that the papery structural map is handled, and treatment step is as follows:
(1), the scanning picture is carried out Flame Image Process, make isoline and background in the papery structural map have tangible aberration;
(2), the available point on the click isoline obtains the search starting point, isoline again as the tail point, are followed the trail of to former and later two directions of this point both as a point then in the search starting point that is obtained;
(3), searching near point, it is poor that the gray-scale value of eight points that will be adjacent with described starting point and the gray-scale value of starting point are done, difference then is considered as gray scale in setting range identical, the close principle of gray-scale value according to the point on the same line, isoline does not have the principle of intersection simultaneously, the identical point of these gray scales then should be on a line, with the neighbor point that the searches starting point as search next time;
(4), some screening, a sampled distance greater than tracked line width is set, with searched for the line between having a few compare with sampled distance respectively, the distance of point-to-point transmission just is preserved for drawing a straight line greater than the point of described sampled distance;
(5), repeating step (2), (3) and (4) descend any search, constantly searches for, satisfy the parameter threshold value that initial user sets and then finish search up in step (2) and (3) and (4), can not find;
(6), the condition when step (2), (3) and (4) does not satisfy, then tracking stops automatically, after tracking is finished automatically, then obtains the numerical information of this papery structural contour map, finish the digitizing of papery structural contour map, the data of generation become the model data of seismic prospecting.
In the described step (3), the gray-scale value of eight points that will be adjacent with described starting point and the gray-scale value of starting point are done difference and are meant: subtract each other the difference of trying to achieve both between the gray-scale value of eight points that will be adjacent with described starting point and the gray-scale value of starting point.
In the described step (3), difference is considered as then in setting range that gray scale is identical to be meant: it is identical then to be considered as gray scale in the difference colourity threshold value that the user sets when program begins.
Compared with prior art, the technique effect that the present invention reached is as follows:
Adopt the said step of the present invention (1) to (6), the technical scheme that forms, be particularly useful at the picture quality of papery structural map relatively good, and the also reasonable situation of the continuity on picture of the isoline in the papery structural map, realized the automatic tracking of papery structural contour map precise and high efficiency, automatically follow the trail of the digitizing that has realized the papery structural contour map after finishing, for seismic prospecting provides a kind of new modeling method.
Description of drawings
The present invention is described in further detail below in conjunction with specification drawings and specific embodiments, wherein:
Fig. 1 is automatic tracing algorithm processing flow chart one by one.
Embodiment
The picture quality that the present invention is directed to the papery structural map is relatively good, and the continuity on picture of the isoline in the papery structural map is also relatively good, adopts automatic one by one tracing algorithm that the papery structural map is handled, and treatment step is as follows:
(1), the scanning picture is carried out Flame Image Process, make isoline and background in the papery structural map have tangible aberration;
(2), the available point on the click isoline obtains the search starting point, isoline again as the tail point, are followed the trail of to former and later two directions of this point both as a point then in the search starting point that is obtained;
(3), searching near point, subtract each other the difference of trying to achieve both between the gray-scale value of eight points that will be adjacent and the gray-scale value of starting point with described starting point, it is identical then to be considered as gray scale in the difference colourity threshold value that the user sets when program begins, the close principle of gray-scale value according to the point on the same line, isoline does not have the principle of intersection simultaneously, the identical point of these gray scales then should be on a line, with the neighbor point that the searches starting point as search next time;
(4), some screening, a sampled distance greater than tracked line width is set, with searched for the line between having a few compare with sampled distance respectively, the distance of point-to-point transmission just is preserved for drawing a straight line greater than the point of described sampled distance;
(5), repeating step (2), (3) and (4) descend any search, constantly searches for, satisfy the parameter threshold value that initial user sets and then finish search up in step (2) and (3) and (4), can not find;
(6), the condition when step (2), (3) and (4) does not satisfy, then tracking stops automatically, after tracking is finished automatically, then obtains the numerical information of this papery structural contour map, finish the digitizing of papery structural contour map, the data of generation become the model data of seismic prospecting.
Claims (3)
1. digital modeling method that is used for seismic prospecting, it is characterized in that: the picture quality at the papery structural map is relatively good, and the continuity on picture of the isoline in the papery structural map is also relatively good, adopt automatic one by one tracing algorithm that the papery structural map is handled, treatment step is as follows:
(1), the scanning picture is carried out Flame Image Process, make isoline and background in the papery structural map have tangible aberration;
(2), the available point on the click isoline obtains the search starting point, isoline again as the tail point, are followed the trail of to former and later two directions of this point both as a point then in the search starting point that is obtained;
(3), searching near point, subtract each other the difference of trying to achieve both between the gray-scale value of eight points that will be adjacent and the gray-scale value of starting point with described starting point, it is identical then to be considered as gray scale in the difference colourity threshold value that the user sets when program begins, the close principle of gray-scale value according to the point on the same line, isoline does not have the principle of intersection simultaneously, the identical point of these gray scales then should be on a line, with the neighbor point that the searches starting point as search next time;
(4), some screening, a sampled distance greater than tracked line width is set, with searched for the line between having a few compare with sampled distance respectively, the distance of point-to-point transmission just is preserved for drawing a straight line greater than the point of described sampled distance;
(5), repeating step (2), (3) and (4) descend any search, constantly searches for, satisfy the parameter threshold value that initial user sets and then finish search up in step (2) and (3) and (4), can not find;
(6), the condition when step (2), (3) and (4) does not satisfy, then tracking stops automatically, after tracking is finished automatically, then obtains the numerical information of this papery structural contour map, finish the digitizing of papery structural contour map, the data of generation become the model data of seismic prospecting.
2. the digital modeling method that is used for seismic prospecting according to claim 1, it is characterized in that: in the described step (3), the gray-scale value of eight points that will be adjacent with described starting point and the gray-scale value of starting point are done difference and are meant: subtract each other the difference of trying to achieve both between the gray-scale value of eight points that will be adjacent with described starting point and the gray-scale value of starting point.
3. the digital modeling method that is used for seismic prospecting according to claim 1 and 2, it is characterized in that: in the described step (3), difference is considered as then in setting range that gray scale is identical to be meant: it is identical then to be considered as gray scale in the difference colourity threshold value that the user sets when program begins.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201010565905 CN101980055B (en) | 2010-11-30 | 2010-11-30 | Digital modeling method for seismic exploration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201010565905 CN101980055B (en) | 2010-11-30 | 2010-11-30 | Digital modeling method for seismic exploration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101980055A true CN101980055A (en) | 2011-02-23 |
| CN101980055B CN101980055B (en) | 2013-05-01 |
Family
ID=43600571
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201010565905 Expired - Fee Related CN101980055B (en) | 2010-11-30 | 2010-11-30 | Digital modeling method for seismic exploration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101980055B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106981084A (en) * | 2016-10-28 | 2017-07-25 | 阿里巴巴集团控股有限公司 | A kind of method and device of drawing isoline |
| CN112099091A (en) * | 2019-06-17 | 2020-12-18 | 中国石油天然气集团有限公司 | Seismic exploration point data static correction method and device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6480790B1 (en) * | 1999-10-29 | 2002-11-12 | Exxonmobil Upstream Research Company | Process for constructing three-dimensional geologic models having adjustable geologic interfaces |
| CN101582173A (en) * | 2009-06-24 | 2009-11-18 | 中国石油集团川庆钻探工程有限公司 | Block model construction method for complex geological structure |
| CN102096102A (en) * | 2010-11-30 | 2011-06-15 | 中国石油集团川庆钻探工程有限公司 | Digital modeling method for seismic exploration |
-
2010
- 2010-11-30 CN CN 201010565905 patent/CN101980055B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6480790B1 (en) * | 1999-10-29 | 2002-11-12 | Exxonmobil Upstream Research Company | Process for constructing three-dimensional geologic models having adjustable geologic interfaces |
| CN101582173A (en) * | 2009-06-24 | 2009-11-18 | 中国石油集团川庆钻探工程有限公司 | Block model construction method for complex geological structure |
| CN102096102A (en) * | 2010-11-30 | 2011-06-15 | 中国石油集团川庆钻探工程有限公司 | Digital modeling method for seismic exploration |
Non-Patent Citations (1)
| Title |
|---|
| 《勘探地球物理进展》 20100228 洪余刚等 多分量地震资料储层预测研究 21-25 1-3 第33卷, 第1期 2 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106981084A (en) * | 2016-10-28 | 2017-07-25 | 阿里巴巴集团控股有限公司 | A kind of method and device of drawing isoline |
| CN106981084B (en) * | 2016-10-28 | 2020-11-06 | 创新先进技术有限公司 | Method and device for drawing contour line |
| CN112099091A (en) * | 2019-06-17 | 2020-12-18 | 中国石油天然气集团有限公司 | Seismic exploration point data static correction method and device |
| CN112099091B (en) * | 2019-06-17 | 2024-03-01 | 中国石油天然气集团有限公司 | Static correction method and device for seismic exploration point data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101980055B (en) | 2013-05-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109709603B (en) | Seismic horizon identification and tracking method and system | |
| CN110609320B (en) | Pre-stack seismic reflection pattern recognition method based on multi-scale feature fusion | |
| CN113642698B (en) | Geophysical well logging intelligent interpretation method, system and storage medium | |
| CN103488971B (en) | Method for identifying geometrical morphology of organic reef storage layer | |
| CN104199092A (en) | Multi-level framework based three-dimensional full-horizon automatic tracking method | |
| CN104155687A (en) | Phase control post-stack acoustic wave impedance inversion method | |
| Wang et al. | An auto-detection network to provide an automated real-time early warning of rock engineering hazards using microseismic monitoring | |
| CN110320557B (en) | Multi-scale geological feature detection fusion method based on deep learning and evolutionary learning | |
| Zhang et al. | Identification of sedimentary facies with well logs: an indirect approach with multinomial logistic regression and artificial neural network | |
| CN105093304A (en) | Method for automatic calculation of lithological curve by employing logging curve in geophysical exploration | |
| Chang et al. | SegLog: Geophysical logging segmentation network for lithofacies identification | |
| CN103969685B (en) | A kind of processing method of thin interbed seismic signal | |
| Zhao et al. | CE-SGAN: Classification enhancement semi-supervised generative adversarial network for lithology identification | |
| CN101980055B (en) | Digital modeling method for seismic exploration | |
| CN102096102B (en) | Digital modeling method for seismic exploration | |
| Pollock et al. | 3D exploratory analysis of descriptive lithology records using regular expressions | |
| CN110988996A (en) | Reservoir porosity prediction method based on Adaboost regression algorithm | |
| CN105277981A (en) | Non-consistent time-lapse seismic bin matching method based on wave field continuation compensation | |
| CN111273346A (en) | Method, device, computer equipment and readable storage medium for removing deposition background | |
| Han et al. | Prediction of igneous lithology and lithofacies based on ensemble learning with data optimization | |
| Zhang et al. | A modified method of multiple point geostatistics for spatial simulation of sedimentary facies for carbonate reservoirs | |
| CN110443801A (en) | A kind of salt dome recognition methods based on improvement AlexNet | |
| CN111290043A (en) | Calculation method of sedimentary stratum pseudo-acoustic logging data | |
| CN110488350B (en) | Seismic inversion big data generation method based on convolutional neural network | |
| CN115828072B (en) | Reconstruction method of missing section of unconventional logging curve and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130501 Termination date: 20181130 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |