CN111583407B - Efficient three-dimensional geological modeling intelligent processing method based on paper drilling - Google Patents
Efficient three-dimensional geological modeling intelligent processing method based on paper drilling Download PDFInfo
- Publication number
- CN111583407B CN111583407B CN202010503589.2A CN202010503589A CN111583407B CN 111583407 B CN111583407 B CN 111583407B CN 202010503589 A CN202010503589 A CN 202010503589A CN 111583407 B CN111583407 B CN 111583407B
- Authority
- CN
- China
- Prior art keywords
- drilling
- stratum
- point
- data
- pinch
- 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.)
- Active
Links
Images
Classifications
-
- 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
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
- G06F16/355—Class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Geometry (AREA)
- Data Mining & Analysis (AREA)
- Medical Informatics (AREA)
- Computational Linguistics (AREA)
- Mathematical Physics (AREA)
- Evolutionary Computation (AREA)
- Databases & Information Systems (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Remote Sensing (AREA)
- Computer Graphics (AREA)
- Excavating Of Shafts Or Tunnels (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a high-efficiency three-dimensional geological modeling intelligent processing method based on paper drilling, which comprises the following steps: step 1, scanning a paper drilling histogram by a form identification method, uniformly archiving the paper drilling histogram into image and text data, and respectively identifying each form data; step 2, summarizing a standard stratum table of geology through machine learning, uniformly importing drilling data into a drilling standard database according to the table, reading drilling data point clouds from the drilling standard database, and generating a geological surface according to a certain rule connecting line; and 3, in the section view intercepted by the model, geological knowledge can be integrated, stratum pinch is processed, improper places are modified and corrected, and drilling data and the change of connecting lines thereof can be synchronized to the geological model in real time. The processing method can reduce errors generated by manual processing, reduce risks and improve the efficiency and accuracy of the whole flow.
Description
Technical Field
The invention relates to the technical field of geological information processing,
in particular, the invention relates to an efficient three-dimensional geological modeling intelligent processing method based on paper drilling.
Background
In the past practical production, the extraction of the drilling information can be completed by manually arranging data from paper documents. Because of the diversity of borehole sources and the different standards of formation and lithology division, the borehole data firstly needs to make a standard formation comparison table according to the geological condition of the region before being used for three-dimensional geological modeling. Even if borehole data is standardized according to a table, interpolation is performed based on formation demarcation points revealed by the borehole, and the obtained geometric model often has a situation of conflict with geological knowledge and needs to be continuously corrected at a later stage. The method for carrying out urban geological three-dimensional geological traditional modeling based on the paper drilling histogram has the defects of higher error rate, low efficiency and the like, so that the process needs to be improved to a certain extent.
The invention Chinese patent CN108335355A provides a geologic body model construction method and device, which belongs to the technical field of geologic information, and the method specifically comprises the following steps: collecting a geological map, drilling data and topographic data, and drawing section lines according to the trend of stratum on the geological map, wherein the section lines do not exceed the boundary of the geological map; processing address information of the area to be modeled according to the section line, the geological map, the drilling data and the topographic data to generate a geological profile; and carrying out model construction on the geological section according to a boundary representation modeling method, determining the positions and the shapes of the surface information, the ring information, the side information and the point information, and generating a geologic body model. The method and the device can automatically generate geological profiles by utilizing visual geological features, different rock layer thicknesses and other information, quickly construct a geologic body model, simplify the workflow of constructing the geologic body model, improve the modeling speed and precision, and facilitate the quick update of the geologic body model. The Chinese patent No. 110058298A provides a three-dimensional geologic body spatial interpolation method and system, wherein the method comprises the steps of data preprocessing, horizon networking, horizon correction, attribute interpolation, attribute correction, layer control body interpolation and the like. The spatial interpolation calculation of the engineering geological properties of multiple wells is realized by spatial matching interpolation based on the seismic amplitude under the control of the interpretation horizon and the well logging data of the well, the spatial spreading of the geological engineering properties based on the seismic body is established, the spatialization and materialization of the geological properties are realized, and the extraction of the property values of any designed well curve is formed. On the basis of three-dimensional visualization, the method can truly and dynamically display various data in the 3D space in a comprehensive mode, has the characteristics of tailorable interpolation constraint information, selectable interpolation method and the like, and compared with the conventional interpolation method at present, the method has the advantages that constraint control conditions are increased on the premise of not increasing operation complexity, interpolation precision is improved, complex interaction in three-dimensional geologic body space interpolation is simplified, operation flow is optimized, and work efficiency is improved.
Although the invention improves the efficiency of three-dimensional geologic modeling to a certain extent, if the invention is applied to the whole process from the extraction of drilling data to the generation of a final model, a process requiring a large amount of manual operation still exists, and a plurality of problems exist.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide an efficient three-dimensional geological modeling intelligent processing method based on paper drilling.
In order to solve the problems, the invention adopts the following technical scheme:
an efficient three-dimensional geological modeling intelligent processing method based on paper drilling comprises the following steps:
step 1, scanning a paper drilling histogram by a form identification method, uniformly archiving the paper drilling histogram into image and text data, and respectively identifying each form data;
step 2, summarizing a standard stratum table of geology through machine learning, uniformly importing drilling data into a drilling standard database according to the table, reading drilling data point clouds from the drilling standard database, and generating a geological surface according to a certain rule connecting line;
and 3, in the section view intercepted by the model, geological knowledge can be integrated, stratum pinch is processed, improper places are modified and corrected, and drilling data and the change of connecting lines thereof can be synchronized to the geological model in real time.
Preferably, in the step 2, the stratum data in the drilling histogram is subjected to stratum standardization by a machine learning method, the recognized drilling stratum sequence is modified according to the standard stratum, geological knowledge is merged, common geological nouns are imported into a corpus in advance to serve as training samples, text classification is carried out on the data in the drilling histogram again by an NLP method, and the results of the two are compared by a traditional machine learning method, so that data with higher confidence is obtained.
Preferably, the treatment method for treating stratum pinch-out in the step 3 is as follows:
aiming at stratum pinch-out conditions, the following parameters are determined according to a profile connecting rule: the length of the connecting line of the crossed stratum in the stacking line diagram, the length from the end point to the crossing point, the length of the stratum section line segment and the distance from the crossing point to the previous stratum are calculated;
generating virtual stratum point cloud data according to the parameter interpolation, connecting adjacent point data, and terminating the connecting behavior when the adjacent point data are prolonged to a non-current stratum; when the stratum thickness is less than 2m, the stratum pinch-out is ignored; when the stratum thickness is between 2m and 5m, the stratum pinch-out control point is positioned at a distance of 1/2 between the current drilling hole and the adjacent drilling hole; when the stratum thickness exceeds 8m, the stratum pinch-out control point is positioned at 2/3 of the current drilling hole and the adjacent drilling hole;
the distance between the formation pinch-out control point and the current borehole is determined according to the following formula:
h represents the formation thickness, d represents the distance between the current borehole and the adjacent borehole, and L represents the distance between the formation pinch-out control point and the current borehole.
Preferably, if points P0 and P1 in the first borehole have no corresponding lithology in the second borehole, there is a formation pinch-out phenomenon; taking the point P as the midpoint of the points P0 and P1, and the point Pn as the midpoint of the adjacent lithology section of the second drilling hole, determining the stratum pinch-out control point Pm between the point P and the point Pn according to the following formula:
wherein xyz is the spatial coordinate of the stratum pinch-out control point Pm, xpypzp is the spatial coordinate of the point P, xnynnzn is the spatial coordinate of the point Pn, and P0, P1, pm, P, pn are lithology separation points of each segment.
Compared with the prior art, the invention has the technical effects that:
according to the efficient three-dimensional geological modeling intelligent processing method based on the paper drilling, on one hand, information in a paper drilling histogram can be rapidly extracted, and stratum data with low confidence coefficient can be standardized and replaced; on the other hand, geological knowledge can be integrated into the modeling process, stratum pinch-out and fault phenomena caused by data errors are reduced, the model is updated in real time, and the rationality of the three-dimensional geological model is improved.
The invention automatically extracts the form of the drilling histogram from the intelligent preprocessing of the paper data, automatically edits and calibrates the profile to a certain extent, and improves the three aspects of data loss, data confusion and data distortion in the traditional geologic model processing; normalizing the borehole formation by a machine learning method; in addition, in the process of three-dimensional geologic modeling, special geologic conditions such as stratum pinch-out and the like can be automatically processed, so that the whole process of generating the three-dimensional geologic model is more intelligent, errors caused by manual processing are reduced, risks are reduced, the efficiency and accuracy of the whole process are improved, researchers can take corresponding processing measures according to the actual conditions of the geologic body, and scientific and reasonable decisions are made.
Drawings
FIG. 1 is a flow chart of an efficient three-dimensional geological modeling intelligent processing method based on paper drilling, which is provided by the embodiment of the invention;
FIG. 2 is a schematic diagram of three-dimensional geologic modeling image processing provided by an embodiment of the invention;
FIG. 3 is a flow chart of borehole formation classification provided in an embodiment of the present invention;
fig. 4 is a diagram of a database structure of drilling criteria according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
A borehole histogram is a composite graph that is compiled to describe the layering, thickness, lithology, structural configuration and contact relationships of a borehole through a formation, groundwater sampling and testing, borehole structure and drilling, etc. The intelligent flow starts from a paper drilling drawing, three steps of drilling data standardization and real-time updating of geological three-dimensional modeling are performed, three-dimensional geological modeling can be achieved without manual operation, an intelligently generated geological model can be changed after geological knowledge is integrated, and the model can be updated synchronously.
The embodiment of the invention provides a high-efficiency three-dimensional geological modeling intelligent processing method based on paper drilling, wherein the processing flow is shown in a figure 1 and comprises the following steps of:
step 1, scanning a paper drilling histogram by a form identification method, uniformly archiving the paper drilling histogram into image and text data, and respectively identifying each form data;
the method comprises the following steps: after the paper drilling data image is obtained through the electronic scanner, preprocessing the image, eliminating deformation in image scanning, extracting key data in the image, unifying the key data into an electronic document, and archiving the electronic document in a form extraction mode, wherein the method comprises the following steps of: obtaining a drilling histogram image, preprocessing the image, identifying a table line, positioning a cell, identifying texts and symbols, correcting the texts and storing data.
Step 2, summarizing a standard stratum table of geology through machine learning, uniformly importing drilling data into a drilling standard database according to the table, reading drilling data point clouds from the drilling standard database (a drilling standard database structure diagram is shown in fig. 4), and generating a geological surface by connecting lines according to a certain rule;
step 2.1, a difficulty exists before data warehouse entry, because of numerous and irregular sources of paper drilling data, a large number of synonyms exist in labels and descriptions in the data, and semantic similar words in the data are required to be processed and replaced uniformly by synonyms recommended to be used under the current standard before warehouse entry. Because of different naming modes and specifications of different departments, the obtained drilling data are inconsistent in number, and before warehouse entry, drilling needs to be renumbered at first, and the flow is approximately as follows:
1) And acquiring all stratum of the drilling data, and eliminating or merging the stratum with the same semantic meaning.
2) And comparing the data of each drilling stratum with all stratum, and designating a standard stratum table according to algorithm and expert guidance so that the overall stratum sequence accords with objective rules.
3) And (3) carrying out iterative processing on the stratum sequence obtained by using the algorithm on all the drilling holes based on the specified standard stratum table so as to uniformly number the drilling holes again.
And 2.2, utilizing machine learning to establish a stratum data corpus according to various geological field data such as engineering geological survey Specification, urban planning engineering geological survey Specification and the like. And performing feature selection on the lithology descriptive contents of the drilling library in the database to obtain a feature set and a total feature dictionary of each stratum category.
And 2.3, word segmentation is carried out on the training set by using a word segmentation tool, then the lithology description is standardized into a stratum result by using a BERT neural network and combining three types of results of original text data, a corpus and word segmentation, combining text labels with two-way identification of the contexts and using a multi-label text classification result. The classification flow of the borehole formation is shown in fig. 3 and includes: reading drill lithology, generating text vectors, generating training files, generating intermediate files, adding a geological corpus, synthesizing training files, and training recognition.
And 3, in the section view intercepted by the model, geological knowledge can be integrated, stratum pinch is processed, improper places are modified and corrected, and drilling data and the change of connecting lines thereof can be synchronized to the geological model in real time.
The treatment method for treating stratum pinch-out comprises the following steps: aiming at stratum pinch-out conditions, the following parameters are determined according to a profile connecting rule: 1. the length of the connecting line of the crossed stratum in the stacking line diagram; 2. calculating the length from the end point to the intersection point; 3. the length of the stratum section line segment; 4. the distance from the intersection to the previous formation.
And generating virtual stratum point cloud data according to the parameter interpolation, connecting adjacent point data, and terminating the connecting behavior when the adjacent point data are prolonged to a non-current stratum. Conventionally, some provision is made for the location of the formation pinch-out: when the stratum thickness is less than 2m, the stratum pinch-out is ignored; when the stratum thickness is between 2m and 5m, the stratum pinch-out control point is positioned at a distance of 1/2 between the current drilling hole and the adjacent drilling hole; when the formation thickness exceeds 8m, the formation pinch-out control point is located at 2/3 of the current borehole and adjacent boreholes.
The distance between the formation pinch-out control point and the current borehole is determined according to the following formula:
h represents the formation thickness, d represents the distance between the current borehole and the adjacent borehole, and L represents the distance between the formation pinch-out control point and the current borehole.
Step 3.2 if point P in the first borehole 0 And P 1 No corresponding lithology exists in the second borehole, and stratum pinch-out phenomenon exists in the second borehole; with point P as point P 0 And P 1 Point P of (2) n Is the midpoint of the adjacent lithology section of the second borehole, the formation pinch-out control point Pm is between point P and point Pn, the formation pinch-out control point P m The determination is made according to the following formula:
wherein xyz is stratum pinch-out control point P m X p y p z p For the P space coordinates of the point, x n y n z n For point P n Spatial coordinates, P 0 、P 1 、P m 、P、P n Is the lithology separation point of each section.
Thus, after the model of the formation pinch is calculated, the position of the borehole connection is modified, which can be synchronized into the three-dimensional geologic model without manual manipulation.
According to the efficient three-dimensional geological modeling intelligent processing method based on the paper drilling, on one hand, information in a paper drilling histogram can be rapidly extracted, and stratum data with low confidence coefficient can be standardized and replaced; on the other hand, geological knowledge can be integrated into the modeling process, stratum pinch-out and fault phenomena caused by data errors are reduced, the model is updated in real time, and the rationality of the three-dimensional geological model is improved.
The invention automatically extracts the form of the drilling histogram from the intelligent preprocessing of the paper data, automatically edits and calibrates the profile to a certain extent, and improves the three aspects of data loss, data confusion and data distortion in the traditional geologic model processing; normalizing the borehole formation by a machine learning method; in addition, in the process of three-dimensional geologic modeling, special geologic conditions such as stratum pinch-out and the like can be automatically processed, so that the whole process of generating the three-dimensional geologic model is more intelligent, errors caused by manual processing are reduced, risks are reduced, the efficiency and accuracy of the whole process are improved, researchers can take corresponding processing measures according to the actual conditions of the geologic body, and scientific and reasonable decisions are made.
The present invention is not limited to the above-described specific embodiments, and various modifications and variations are possible. Any modification, equivalent replacement, improvement, etc. of the above embodiments according to the technical substance of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. An efficient three-dimensional geological modeling intelligent processing method based on paper drilling is characterized by comprising the following steps of:
step 1, scanning a paper drilling histogram to form a picture, and respectively carrying out table text information recognition extraction and archiving treatment on the drilling histogram picture by a table recognition method;
step 2, using the drilling histogram stratum data subjected to synonym unified replacement processing as input parameters of a machine learning model, summarizing a standard stratum table of geology through machine learning, uniformly importing the drilling data into a drilling standard database according to the table, reading drilling data point clouds from the drilling standard database, and generating a geological profile by connecting lines according to a certain rule;
and step 3, integrating geological knowledge into the sectional view, processing stratum pinch-out, and synchronizing the change of drilling data and the connection line thereof to a geological model in real time.
2. The efficient three-dimensional geologic modeling intelligent processing method based on paper drilling according to claim 1, wherein in the step 2, stratum data in a drilling histogram is subjected to stratum standardization by a machine learning-based method, the recognized drilling stratum sequence is modified according to a standard stratum, geological knowledge is merged, commonly used geologic nouns are imported into a corpus in advance to serve as training samples, text classification is conducted on data in the drilling histogram again by an NLP method, and results of the two are compared by a traditional machine learning method, so that data with higher confidence is obtained.
3. The method for intelligent processing of three-dimensional geological modeling based on paper drilling with high efficiency according to claim 1, wherein the processing method for processing stratum pinch-out in the step 3 is as follows:
aiming at stratum pinch-out conditions, the following parameters are determined according to a profile connecting rule: the length of the connecting line of the crossed stratum in the stacking line diagram, the length from the end point to the crossing point, the length of the stratum section line segment and the distance from the crossing point to the previous stratum are calculated;
generating virtual stratum point cloud data according to the parameter interpolation, connecting adjacent point data, and terminating the connecting behavior when the adjacent point data are prolonged to a non-current stratum; when the stratum thickness is smaller than 2m, the stratum pinch-out control point is positioned at a distance of 1/4 between the current drilling hole and the adjacent drilling hole; when the stratum thickness is between 2m and 5m, the stratum pinch-out control point is positioned at a distance of 1/3 between the current drilling hole and the adjacent drilling hole; when the stratum thickness is between 5m and 8m, the stratum pinch-out control point is positioned at a distance of 1/2 between the current drilling hole and the adjacent drilling hole; when the stratum thickness exceeds 8m, the stratum pinch-out control point is positioned at 2/3 of the current drilling hole and the adjacent drilling hole;
the distance between the formation pinch-out control point and the current borehole is determined according to the following formula:
h represents the formation thickness, d represents the distance between the current borehole and the adjacent borehole, and L represents the distance between the formation pinch-out control point and the current borehole.
4. An efficient three-dimensional geologic modeling intelligent processing method based on paper drilling as defined in claim 3, wherein if point P in the first borehole 0 And P 1 No corresponding lithology exists in the second borehole, and stratum pinch-out phenomenon exists in the second borehole; with point P as point P 0 And P 1 Point P of (2) n Is the midpoint of the adjacent lithology section of the second borehole, the formation pinch-out control point Pm is between point P and point Pn, the formation pinch-out control point P m The determination is made according to the following formula:
wherein x, y and z are stratum pinch-out control points P m X p 、y p 、z p For the P space coordinates of the point, x n 、y n 、z n For point P n Spatial coordinates, P 0 、P 1 、P m 、P、P n Is the lithology separation point of each section.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010503589.2A CN111583407B (en) | 2020-06-05 | 2020-06-05 | Efficient three-dimensional geological modeling intelligent processing method based on paper drilling |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010503589.2A CN111583407B (en) | 2020-06-05 | 2020-06-05 | Efficient three-dimensional geological modeling intelligent processing method based on paper drilling |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111583407A CN111583407A (en) | 2020-08-25 |
| CN111583407B true CN111583407B (en) | 2023-05-12 |
Family
ID=72111167
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010503589.2A Active CN111583407B (en) | 2020-06-05 | 2020-06-05 | Efficient three-dimensional geological modeling intelligent processing method based on paper drilling |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111583407B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220098972A1 (en) * | 2020-09-25 | 2022-03-31 | Halliburton Energy Services, Inc. | Correcting borehole images using machine-learning models |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112800158B (en) * | 2021-01-19 | 2022-09-13 | 吉林大学 | Vectorization representation method of geological map |
| CN112907743B (en) * | 2021-03-08 | 2022-05-06 | 中南大学 | Geological body section/plane automatic mapping method, device, equipment and medium |
| CN114528280A (en) * | 2021-12-31 | 2022-05-24 | 济南轨道交通集团有限公司 | Auxiliary standardization method for original layering of drill holes |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106097445A (en) * | 2016-06-02 | 2016-11-09 | 广州市设计院 | A kind of method for drafting of novel three-dimensional stratum curved surface |
| CN106709988A (en) * | 2015-11-16 | 2017-05-24 | 天津市勘察院 | Construction method of engineering geological section map |
| CN106777391A (en) * | 2017-02-21 | 2017-05-31 | 河海大学 | Geologic section modeling method based on drill hole information and knowledge reasoning technology |
| CN108335355A (en) * | 2018-02-28 | 2018-07-27 | 武汉智博创享科技股份有限公司 | A kind of model of geological structure body construction method and device |
| CN110689615A (en) * | 2019-10-18 | 2020-01-14 | 中交 (天津) 生态环保设计研究院有限公司 | Parameterized three-dimensional geological modeling method and system and information data processing terminal |
| CN110826393A (en) * | 2019-09-17 | 2020-02-21 | 中国地质大学（武汉） | Efficient automatic extraction method for drilling histogram information |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8793113B2 (en) * | 2010-05-14 | 2014-07-29 | Schlumberger Technology Corporation | Method and apparatus for near well structural modeling based on borehole dips |
| US20140081613A1 (en) * | 2011-11-01 | 2014-03-20 | Austin Geomodeling, Inc. | Method, system and computer readable medium for scenario mangement of dynamic, three-dimensional geological interpretation and modeling |
| WO2017165949A1 (en) * | 2016-03-30 | 2017-10-05 | Nexen Energy Ulc | Methods, systems and devices for modelling reservoir properties |
-
2020
- 2020-06-05 CN CN202010503589.2A patent/CN111583407B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106709988A (en) * | 2015-11-16 | 2017-05-24 | 天津市勘察院 | Construction method of engineering geological section map |
| CN106097445A (en) * | 2016-06-02 | 2016-11-09 | 广州市设计院 | A kind of method for drafting of novel three-dimensional stratum curved surface |
| CN106777391A (en) * | 2017-02-21 | 2017-05-31 | 河海大学 | Geologic section modeling method based on drill hole information and knowledge reasoning technology |
| CN108335355A (en) * | 2018-02-28 | 2018-07-27 | 武汉智博创享科技股份有限公司 | A kind of model of geological structure body construction method and device |
| CN110826393A (en) * | 2019-09-17 | 2020-02-21 | 中国地质大学（武汉） | Efficient automatic extraction method for drilling histogram information |
| CN110689615A (en) * | 2019-10-18 | 2020-01-14 | 中交 (天津) 生态环保设计研究院有限公司 | Parameterized three-dimensional geological modeling method and system and information data processing terminal |
Non-Patent Citations (1)
| Title |
|---|
| 张军强."水电工程多尺度三维地质建模及分析技术研究".《中国博士学位论文全文数据库》.2016,(第03期),全文. * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220098972A1 (en) * | 2020-09-25 | 2022-03-31 | Halliburton Energy Services, Inc. | Correcting borehole images using machine-learning models |
| US11898435B2 (en) * | 2020-09-25 | 2024-02-13 | Halliburton Energy Services, Inc. | Correcting borehole images using machine-learning models |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111583407A (en) | 2020-08-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111583407B (en) | Efficient three-dimensional geological modeling intelligent processing method based on paper drilling | |
| CN109710701A (en) | A kind of automated construction method for public safety field big data knowledge mapping | |
| CN111950051B (en) | BIM-based three-dimensional geological modeling and geological model-based construction application method | |
| CN111046462A (en) | Drawing display system and method for outdoor building design | |
| CN110134724A (en) | A kind of the data intelligence extraction and display system and method for Building Information Model | |
| CN111950046B (en) | Drilling data model construction method based on BIM | |
| CN104091005B (en) | A kind of Overhead Line Project measures indoor and field integration system | |
| CN110211231B (en) | Three-dimensional geological disaster information model modeling method | |
| CN109597129B (en) | fracture-cavity type oil reservoir beaded reflection characteristic identification method based on target detection | |
| CN112651289A (en) | Intelligent identification and verification system and method for value-added tax common invoice | |
| CN104077447A (en) | Urban three-dimensional space vector modeling method based on paper plane data | |
| CN105205864A (en) | Multi-source-data-based automatic modeling method and system of three-dimension model of geological structural surface | |
| CN108959204B (en) | Internet financial project information extraction method and system | |
| CN106202156A (en) | The log sheet of a kind of sing on web generalized information system generates method online | |
| CN109033132A (en) | The method and device of text and the main body degree of correlation are calculated using knowledge mapping | |
| CN110070087A (en) | Image identification method and device | |
| CN111367911A (en) | Site environment data analysis method and system | |
| CN106569272A (en) | Earthquake attribute fusion method based on data property space ascending dimension | |
| CN110826393B (en) | Automatic extraction method of drilling histogram information | |
| CN117151659B (en) | Ecological restoration engineering full life cycle tracing method based on large language model | |
| CN106530109A (en) | Oilfield development appraisal well decision method based on information value | |
| CN111159411A (en) | Knowledge graph fused text position analysis method, system and storage medium | |
| CN115205886A (en) | Method and device for extracting borehole stratum information, electronic equipment and storage medium | |
| CN107194966B (en) | Identification method for geological boundary and attribute information of two-dimensional geological section map | |
| CN106504319B (en) | Reservoir Three Dimensional Contrast map generalization method and device between well |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |