SG11201501141UA - Systems and methods for 3d seismic data depth conversion utilizing artificial neural networks - Google Patents
Systems and methods for 3d seismic data depth conversion utilizing artificial neural networksInfo
- Publication number
- SG11201501141UA SG11201501141UA SG11201501141UA SG11201501141UA SG11201501141UA SG 11201501141U A SG11201501141U A SG 11201501141UA SG 11201501141U A SG11201501141U A SG 11201501141UA SG 11201501141U A SG11201501141U A SG 11201501141UA SG 11201501141U A SG11201501141U A SG 11201501141UA
- Authority
- SG
- Singapore
- Prior art keywords
- systems
- methods
- neural networks
- seismic data
- artificial neural
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/32—Transforming one recording into another or one representation into another
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/282—Application of seismic models, synthetic seismograms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/301—Analysis for determining seismic cross-sections or geostructures
- G01V1/302—Analysis for determining seismic cross-sections or geostructures in 3D data cubes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/40—Transforming data representation
- G01V2210/48—Other transforms
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/64—Geostructures, e.g. in 3D data cubes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/66—Subsurface modeling
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/US2012/067989 WO2014088571A1 (en) | 2012-12-05 | 2012-12-05 | Systems and methods for 3d seismic data depth conversion utilizing artificial neural networks |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| SG11201501141UA true SG11201501141UA (en) | 2015-03-30 |
Family
ID=50883829
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| SG11201501141UA SG11201501141UA (en) | 2012-12-05 | 2012-12-05 | Systems and methods for 3d seismic data depth conversion utilizing artificial neural networks |
Country Status (9)
| Country | Link |
|---|---|
| US (1) | US20150316673A1 (en) |
| EP (1) | EP2888606B1 (en) |
| CN (1) | CN104884974A (en) |
| AU (1) | AU2012396293B2 (en) |
| CA (1) | CA2890187C (en) |
| MX (1) | MX2015005627A (en) |
| RU (1) | RU2015110010A (en) |
| SG (1) | SG11201501141UA (en) |
| WO (1) | WO2014088571A1 (en) |
Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014200669A2 (en) | 2013-06-10 | 2014-12-18 | Exxonmobil Upstream Research Company | Determining well parameters for optimization of well performance |
| WO2016060645A1 (en) * | 2014-10-14 | 2016-04-21 | Landmark Graphics Corporation | Using representative elemental volume to determine subset volume in an area of interest earth model |
| CN106094028A (en) * | 2016-06-22 | 2016-11-09 | 中国石油化工股份有限公司 | Depth Domain seismic attribute extracting method based on displacement field |
| CN105974475B (en) * | 2016-06-24 | 2018-02-06 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | A kind of time and depth transfer method |
| CN106873033B (en) * | 2017-03-13 | 2019-03-22 | 中国海洋石油集团有限公司 | A kind of method of more attribute earthquake information fusion FRACTURE PREDICTIONs neural network based |
| US11231513B2 (en) * | 2017-12-06 | 2022-01-25 | Chevron U.S.A. Inc. | Systems and methods for refining estimated parameter values in seismic imaging |
| CN108490491A (en) * | 2018-03-06 | 2018-09-04 | 中国石油集团东方地球物理勘探有限责任公司 | A kind of beach body prediction technique indicating inverting based on waveform |
| CN110837111B (en) * | 2018-08-15 | 2021-08-24 | 中国石油化工股份有限公司 | Seismic data interpolation method and system |
| CN112346117B (en) * | 2019-08-09 | 2023-06-30 | 中国石油天然气集团有限公司 | Reservoir characteristic prediction method and device based on seismic attribute fusion |
| US11169287B2 (en) | 2020-03-27 | 2021-11-09 | Saudi Arabian Oil Company | Method and system for automated velocity model updating using machine learning |
| US11614557B2 (en) * | 2020-04-07 | 2023-03-28 | Landmark Graphics Corporation | Data-driven domain conversion using machine learning techniques |
| CA3107816C (en) * | 2020-04-07 | 2023-08-15 | Landmark Graphics Corporation | Data-driven domain conversion using machine learning techniques |
| CN113589363B (en) * | 2020-04-30 | 2024-03-19 | 中国石油化工股份有限公司 | Novel oil gas prediction method integrating artificial neural network and geostatistics |
| CN111983691B (en) * | 2020-08-18 | 2023-10-13 | 郑州市混沌信息技术有限公司 | Reservoir prediction method and software system with multi-model fusion |
| CA3221405A1 (en) * | 2021-05-27 | 2022-12-01 | Schlumberger Canada Limited | Seismic well tie based on machine learning |
| US11668848B2 (en) | 2021-06-24 | 2023-06-06 | Saudi Arabian Oil Company | Method and system for seismic imaging using S-wave velocity models and machine learning |
| US11874419B2 (en) * | 2021-06-30 | 2024-01-16 | Saudi Arabian Oil Company | System and method for automated domain conversion for seismic well ties |
| CN113671568B (en) * | 2021-08-20 | 2022-07-15 | 中国科学院武汉岩土力学研究所 | Disturbance stress-microseism simultaneous time-space integrated sensing system and method |
| US20230184975A1 (en) * | 2021-12-15 | 2023-06-15 | Saudi Arabian Oil Company | Method and system for determining seismic velocities using global path tracing |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060047429A1 (en) * | 2004-08-24 | 2006-03-02 | Adams Steven L | Method of estimating geological formation depths by converting interpreted seismic horizons from the time domain to the depth domain |
| US7613665B2 (en) * | 2005-06-24 | 2009-11-03 | Halliburton Energy Services, Inc. | Ensembles of neural networks with different input sets |
| US7525874B2 (en) * | 2006-04-21 | 2009-04-28 | Prism Seismic Inc. | Method for converting seismic data from the time domain to the depth domain |
| MY164574A (en) * | 2008-05-22 | 2018-01-15 | Exxonmobil Upstream Res Co | Seismic horizon skeletonization |
| GB0820377D0 (en) * | 2008-11-07 | 2008-12-17 | Isis Innovation | Mapping and characterization of cavitation activity |
| CN102147479B (en) * | 2011-01-11 | 2013-05-29 | 中国海洋石油总公司 | Modelling method of reservoir space physical property parameters |
| BR112013016699A2 (en) * | 2011-01-13 | 2016-10-04 | Landmark Graphics Corp | method, computer system, and computer readable media |
| EP2671167A4 (en) * | 2011-01-31 | 2018-01-31 | Landmark Graphics Corporation | System and method for using an artificial neural network to simulate pipe hydraulics in a reservoir simulator |
| CN102565853A (en) * | 2011-12-20 | 2012-07-11 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Method for modeling velocity model of geologic structure |
-
2012
- 2012-12-05 MX MX2015005627A patent/MX2015005627A/en unknown
- 2012-12-05 CA CA2890187A patent/CA2890187C/en active Active
- 2012-12-05 RU RU2015110010A patent/RU2015110010A/en not_active Application Discontinuation
- 2012-12-05 WO PCT/US2012/067989 patent/WO2014088571A1/en active Application Filing
- 2012-12-05 AU AU2012396293A patent/AU2012396293B2/en not_active Ceased
- 2012-12-05 CN CN201280076880.XA patent/CN104884974A/en active Pending
- 2012-12-05 US US14/646,836 patent/US20150316673A1/en not_active Abandoned
- 2012-12-05 EP EP12889428.4A patent/EP2888606B1/en active Active
- 2012-12-05 SG SG11201501141UA patent/SG11201501141UA/en unknown
Also Published As
| Publication number | Publication date |
|---|---|
| RU2015110010A (en) | 2017-01-11 |
| CA2890187C (en) | 2018-11-06 |
| EP2888606A1 (en) | 2015-07-01 |
| EP2888606B1 (en) | 2019-11-13 |
| WO2014088571A1 (en) | 2014-06-12 |
| CA2890187A1 (en) | 2014-06-12 |
| AU2012396293B2 (en) | 2016-04-21 |
| CN104884974A (en) | 2015-09-02 |
| MX2015005627A (en) | 2016-02-03 |
| AU2012396293A1 (en) | 2015-03-19 |
| US20150316673A1 (en) | 2015-11-05 |
| EP2888606A4 (en) | 2016-07-27 |
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