JP7354268B2 - 人工知能を使った地震属性の高速算出のための方法 - Google Patents
人工知能を使った地震属性の高速算出のための方法 Download PDFInfo
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- JP7354268B2 JP7354268B2 JP2021549110A JP2021549110A JP7354268B2 JP 7354268 B2 JP7354268 B2 JP 7354268B2 JP 2021549110 A JP2021549110 A JP 2021549110A JP 2021549110 A JP2021549110 A JP 2021549110A JP 7354268 B2 JP7354268 B2 JP 7354268B2
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- 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. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/60—Image enhancement or restoration using machine learning, e.g. neural networks
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/77—Retouching; Inpainting; Scratch removal
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- Computational Linguistics (AREA)
- Software Systems (AREA)
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- Health & Medical Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201962807881P | 2019-02-20 | 2019-02-20 | |
| US62/807,881 | 2019-02-20 | ||
| US16/788,500 | 2020-02-12 | ||
| US16/788,500 US11009617B2 (en) | 2019-02-20 | 2020-02-12 | Method for fast calculation of seismic attributes using artificial intelligence |
| PCT/US2020/017916 WO2020172019A1 (en) | 2019-02-20 | 2020-02-12 | Method for fast calculation of seismic attributes using artificial intelligence |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2022520994A JP2022520994A (ja) | 2022-04-04 |
| JP2022520994A5 JP2022520994A5 (https=) | 2023-02-17 |
| JP7354268B2 true JP7354268B2 (ja) | 2023-10-02 |
Family
ID=72040619
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021549110A Active JP7354268B2 (ja) | 2019-02-20 | 2020-02-12 | 人工知能を使った地震属性の高速算出のための方法 |
Country Status (4)
| Country | Link |
|---|---|
| US (1) | US11009617B2 (https=) |
| EP (1) | EP3928131A1 (https=) |
| JP (1) | JP7354268B2 (https=) |
| WO (1) | WO2020172019A1 (https=) |
Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US12425605B2 (en) * | 2018-03-21 | 2025-09-23 | Nvidia Corporation | Image in-painting for irregular holes using partial convolutions |
| WO2021020982A1 (en) | 2019-07-31 | 2021-02-04 | Saudi Arabian Oil Company | Enhancement of seismic data |
| US12123994B2 (en) | 2019-07-31 | 2024-10-22 | Saudi Arabian Oil Company | Enhancement of seismic data |
| US12123993B2 (en) | 2019-07-31 | 2024-10-22 | Saudi Arabian Oil Company | Enhancement of seismic data |
| WO2021245563A1 (en) * | 2020-06-02 | 2021-12-09 | Matrix Jvco Ltd | Borehole image interpretation and analysis |
| EP4211500A1 (en) | 2020-09-07 | 2023-07-19 | Saudi Arabian Oil Company | Enhancement of single sensor seismic data |
| CN114428271A (zh) * | 2020-10-09 | 2022-05-03 | 中国石油化工股份有限公司 | 一种基于深度学习的地震数据重建方法及系统 |
| CN112083498B (zh) * | 2020-10-16 | 2021-05-25 | 山东科技大学 | 一种基于深度神经网络的多波地震油气储层预测方法 |
| CN112881986B (zh) * | 2021-01-15 | 2022-08-23 | 电子科技大学 | 基于优化深度模型的雷达切片存储转发式干扰抑制方法 |
| US12032111B2 (en) | 2021-03-05 | 2024-07-09 | Saudi Arabian Oil Company | Method and system for faster seismic imaging using machine learning |
| CN114047548B (zh) * | 2021-07-07 | 2023-03-14 | 清华大学 | 一种基于闭环网络的地震波阻抗反演不确定性的预测方法 |
| US12013508B2 (en) | 2021-10-28 | 2024-06-18 | Saudi Arabian Oil Company | Method and system for determining seismic processing parameters using machine learning |
| US20230229908A1 (en) * | 2022-01-18 | 2023-07-20 | Aramco Overseas Company B.V. | Methods and systems for an online machine-learned non-linear beamforming tuple solver |
| KR102550707B1 (ko) * | 2022-10-12 | 2023-06-30 | 부경대학교 산학협력단 | 딥러닝 기반 경사지 균열 감지 방법과 이를 이용한 산사태 조기 감지 방법 및 그 장치 |
| CN115661653B (zh) * | 2022-11-01 | 2025-11-18 | 中国科学院合肥物质科学研究院 | 一种基于脱色方法的农作物高光谱图像可视化检测方法 |
| CN115828151A (zh) * | 2022-11-04 | 2023-03-21 | 湖州师范学院 | 一种基于局部知识增强的深度集成方法 |
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| JP2004029361A (ja) | 2002-06-25 | 2004-01-29 | Canon Inc | 画像形成装置 |
| JP2014535044A (ja) | 2011-09-28 | 2014-12-25 | サウジ アラビアン オイル カンパニー | 最小二乗サポートベクターマシンを用いた貯留層特性予測 |
| US20150032426A1 (en) | 2013-07-29 | 2015-01-29 | Chevron U.S.A. Inc. | System and method for estimating a reservoir parameter using joint stochastic inversion of multisource geophysical data |
| JP2018048898A (ja) | 2016-09-21 | 2018-03-29 | 日本電気株式会社 | 画像処理装置、画像処理方法及びプログラム |
| WO2018148492A1 (en) | 2017-02-09 | 2018-08-16 | Schlumberger Technology Corporation | Geophysical deep learning |
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| JP2878409B2 (ja) * | 1989-09-04 | 1999-04-05 | 株式会社リコー | 3次元物体撮像方式 |
| US5453958A (en) * | 1993-06-11 | 1995-09-26 | Phillips Petroleum Company | Method for locating hydrocarbon reservoirs |
| US5930730A (en) * | 1994-12-12 | 1999-07-27 | Amoco Corporation | Method and apparatus for seismic signal processing and exploration |
| US6226596B1 (en) * | 1999-10-27 | 2001-05-01 | Marathon Oil Company | Method for analyzing and classifying three dimensional seismic information |
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| US7218573B1 (en) * | 2006-01-06 | 2007-05-15 | Westerngeco, L.L.C. | Interpretation of shot gather and stack of seismic data |
| WO2010080366A1 (en) * | 2009-01-09 | 2010-07-15 | Exxonmobil Upstream Research Company | Hydrocarbon detection with passive seismic data |
| CA2810540C (en) * | 2012-03-28 | 2020-06-16 | Schlumberger Canada Limited | Seismic attribute color model transform |
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| EP3418778B1 (en) * | 2013-03-15 | 2020-07-15 | Emerson Paradigm Holding LLC | Systems and methods to build sedimentary attributes |
| US9977996B2 (en) * | 2013-06-24 | 2018-05-22 | Schlumberger Technology Corporation | Characterizing porosity distribution from a borehole image |
| US10663609B2 (en) * | 2013-09-30 | 2020-05-26 | Saudi Arabian Oil Company | Combining multiple geophysical attributes using extended quantization |
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2020
- 2020-02-12 WO PCT/US2020/017916 patent/WO2020172019A1/en not_active Ceased
- 2020-02-12 EP EP20712102.1A patent/EP3928131A1/en not_active Withdrawn
- 2020-02-12 JP JP2021549110A patent/JP7354268B2/ja active Active
- 2020-02-12 US US16/788,500 patent/US11009617B2/en active Active
Patent Citations (5)
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| JP2004029361A (ja) | 2002-06-25 | 2004-01-29 | Canon Inc | 画像形成装置 |
| JP2014535044A (ja) | 2011-09-28 | 2014-12-25 | サウジ アラビアン オイル カンパニー | 最小二乗サポートベクターマシンを用いた貯留層特性予測 |
| US20150032426A1 (en) | 2013-07-29 | 2015-01-29 | Chevron U.S.A. Inc. | System and method for estimating a reservoir parameter using joint stochastic inversion of multisource geophysical data |
| JP2018048898A (ja) | 2016-09-21 | 2018-03-29 | 日本電気株式会社 | 画像処理装置、画像処理方法及びプログラム |
| WO2018148492A1 (en) | 2017-02-09 | 2018-08-16 | Schlumberger Technology Corporation | Geophysical deep learning |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2022520994A (ja) | 2022-04-04 |
| EP3928131A1 (en) | 2021-12-29 |
| US20200264327A1 (en) | 2020-08-20 |
| WO2020172019A1 (en) | 2020-08-27 |
| US11009617B2 (en) | 2021-05-18 |
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