CA2604738A1 - Well logging with reduced usage of radioisotopic sources - Google Patents
Well logging with reduced usage of radioisotopic sources Download PDFInfo
- Publication number
- CA2604738A1 CA2604738A1 CA002604738A CA2604738A CA2604738A1 CA 2604738 A1 CA2604738 A1 CA 2604738A1 CA 002604738 A CA002604738 A CA 002604738A CA 2604738 A CA2604738 A CA 2604738A CA 2604738 A1 CA2604738 A1 CA 2604738A1
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- Prior art keywords
- log
- logs
- radioisotopic
- well bore
- tool
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- 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
- G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- 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
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
Abstract
Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool;
and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
Claims (28)
1. A method that comprises:
collecting at least one output log of a first well bore from measurements with a radioisotopic source;
collecting at least one input log of the first well bore from measurements by a non-radioisotopic logging tool;
training a neural network to predict the output log from the at least one input log;
collecting at least one input log of a second well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the second well bore to synthesize at least one output log of the second well bore.
collecting at least one output log of a first well bore from measurements with a radioisotopic source;
collecting at least one input log of the first well bore from measurements by a non-radioisotopic logging tool;
training a neural network to predict the output log from the at least one input log;
collecting at least one input log of a second well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the second well bore to synthesize at least one output log of the second well bore.
2. The method of claim 1, further comprising:
selecting at least one well completion location based at least in part on the at least one output log of the second well bore; and perforating well bore casing at the at least one well completion location.
selecting at least one well completion location based at least in part on the at least one output log of the second well bore; and perforating well bore casing at the at least one well completion location.
3. The method of claim 2, wherein the processing operation provides a density log and a neutron porosity log of the second well bore, and wherein the selecting operation comprises identifying cross-over intervals of the density and neutron porosity logs.
4. The method of claim 1, wherein the first well bore is a training well bore and the second well bore is a development well bore.
5. The method of claim 1, wherein the at least one input log collected from the first and second well bores comprises an open hole log and a cased hole log.
6. The method of claim 5, wherein the cased hole log is determined from measurements by a pulsed neutron capture logging tool.
7. The method of claim 5, wherein the cased hole log comprises a log in a set consisting of resistivity logs, sonic logs, gamma ray spectroscopy logs, production logs, and combinations thereof.
8. The method of claim 5, wherein the open hole log comprises a log in a set consisting of resistivity logs, sonic logs, nuclear magnetic resonance logs, gamma ray spectroscopy logs, spontaneous potential logs, and combinations thereof.
9. The method of claim 1, wherein the at least one output log comprises at least one of a log of neutron porosity and a log of formation density.
10. The method of claim 1, wherein the at least one input log comprises at least one of a log indicative of formation resisitivity and a sonic log.
11. The method of claim 1, wherein the at least one input log comprises a log in a set consisting of natural gamma ray logs, induced gamma ray logs, sonic logs, nuclear magnetic resonance logs, and combinations thereof.
12. The method of claim 1, wherein the non-radioisotopic logging tool comprises a pulsed neutron source.
13. The method of claim 12, wherein the non-radioisotopic logging tool is a cased hole logging tool.
14. The method of claim 12, wherein the non-radioisotopic logging tool is a logging while drilling tool.
15. An information carrier medium that, when placed in operable relation to a computer, provides the computer with software comprising:
a training process that generates a neural network for synthesizing one or more radioisotopic logging tool logs; and a transform process that applies the neural network to convert an input set of non-radioisotopic logging tool logs into an output set of one or more predicted radioisotopic logging tool logs.
a training process that generates a neural network for synthesizing one or more radioisotopic logging tool logs; and a transform process that applies the neural network to convert an input set of non-radioisotopic logging tool logs into an output set of one or more predicted radioisotopic logging tool logs.
16. The medium of claim 15, wherein the neural network is part of a neural network ensemble, wherein the training process generates a set of neural networks having diversity in inputs and in complexity, and wherein the software further comprises:
a selection process that identifies a combination of neural networks from the set of neural networks to form the neural network ensemble.
a selection process that identifies a combination of neural networks from the set of neural networks to form the neural network ensemble.
17. The medium of claim 15, wherein the output set comprises at least one of a neutron porosity log and a density log.
18. The medium of claim 15, wherein the input set comprises a resistivity log and logs by a pulsed neutron logging tool.
19. The medium of claim 18, wherein the pulsed neutron logging tool is a cased hole logging tool.
20. The medium of claim 16, wherein the selection process identifies a combination of neural networks from the set having a desirable fitness measure, said fitness measure being based at least in part on a measure of negative correlation for each neural network in the combination.
21. A system that comprises:
a non-radioisotopic logging tool to obtain measurements in a well bore; and a computer to receive the measurements from the non-radioisotopic logging tool, wherein the computer synthesizes at least one of a density log and a neutron porosity log using the measurements from the non-radioisotopic logging tool.
a non-radioisotopic logging tool to obtain measurements in a well bore; and a computer to receive the measurements from the non-radioisotopic logging tool, wherein the computer synthesizes at least one of a density log and a neutron porosity log using the measurements from the non-radioisotopic logging tool.
22. The system of claim 21, wherein the computer implements a neural network to convert multiple non-radioisotopic logs into at least one of a density log and a neutron porosity log.
23. The system of claim 22, further comprising a perforation tool to perforate casing in the well bore at positions selected based at least in part on at least one of a density log and a neutron porosity log synthesized by the computer.
24. A logging method that comprises:
obtaining a first log of a well bore by at least one of a resistivity tool and a sonic tool;
obtaining a pulsed neutron tool log of the well bore; and combining the first log with the pulsed neutron tool log to synthesize a radioisotopic source tool log of the well bore.
obtaining a first log of a well bore by at least one of a resistivity tool and a sonic tool;
obtaining a pulsed neutron tool log of the well bore; and combining the first log with the pulsed neutron tool log to synthesize a radioisotopic source tool log of the well bore.
25. The logging method of claim 24, wherein the combining operation employs a neural network ensemble to synthesize the radioisotopic source tool log.
26. The logging method of claim 24, wherein the radioisotopic source tool log is a neutron porosity log.
27. The logging method of claim 24, wherein the radioisotopic source tool log is a density log.
28. The logging method of claim 24, wherein the first log is a resistivity log.
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US11/165,892 | 2005-06-24 | ||
| US11/165,892 US7613665B2 (en) | 2005-06-24 | 2005-06-24 | Ensembles of neural networks with different input sets |
| US11/270,284 US7587373B2 (en) | 2005-06-24 | 2005-11-09 | Neural network based well log synthesis with reduced usage of radioisotopic sources |
| US11/270,284 | 2005-11-09 | ||
| PCT/US2006/025029 WO2007002693A2 (en) | 2005-06-24 | 2006-06-26 | Well logging with reduced usage of radioisotopic sources |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CA2604738A1 true CA2604738A1 (en) | 2007-01-04 |
| CA2604738C CA2604738C (en) | 2011-11-15 |
Family
ID=37595990
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2604738A Expired - Fee Related CA2604738C (en) | 2005-06-24 | 2006-06-26 | Well logging with reduced usage of radioisotopic sources |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US7587373B2 (en) |
| AU (1) | AU2006261707B2 (en) |
| BR (1) | BRPI0611579A2 (en) |
| CA (1) | CA2604738C (en) |
| GB (1) | GB2441463B (en) |
| WO (1) | WO2007002693A2 (en) |
Families Citing this family (41)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8374974B2 (en) * | 2003-01-06 | 2013-02-12 | Halliburton Energy Services, Inc. | Neural network training data selection using memory reduced cluster analysis for field model development |
| US7587373B2 (en) | 2005-06-24 | 2009-09-08 | Halliburton Energy Services, Inc. | Neural network based well log synthesis with reduced usage of radioisotopic sources |
| US7613665B2 (en) * | 2005-06-24 | 2009-11-03 | Halliburton Energy Services, Inc. | Ensembles of neural networks with different input sets |
| US8065244B2 (en) * | 2007-03-14 | 2011-11-22 | Halliburton Energy Services, Inc. | Neural-network based surrogate model construction methods and applications thereof |
| US7791017B2 (en) * | 2007-07-23 | 2010-09-07 | Schlumberger Technology Corporation | Method to simultaneously determine pore hydrocarbon density and water saturation from pulsed neutron measurements |
| CA2638593A1 (en) * | 2007-08-16 | 2009-02-16 | Andrew Echenberg | Online magazine |
| US8417495B2 (en) * | 2007-11-07 | 2013-04-09 | Baker Hughes Incorporated | Method of training neural network models and using same for drilling wellbores |
| US20090182693A1 (en) * | 2008-01-14 | 2009-07-16 | Halliburton Energy Services, Inc. | Determining stimulation design parameters using artificial neural networks optimized with a genetic algorithm |
| US8234072B2 (en) * | 2008-02-20 | 2012-07-31 | Carbo Ceramics, Inc | Methods of identifying high neutron capture cross section doped proppant in induced subterranean formation fractures |
| US8214151B2 (en) * | 2008-02-20 | 2012-07-03 | Carbo Ceramics Inc. | Methods of identifying high neutron capture cross section doped proppant in induced subterranean formation fractures |
| US8100177B2 (en) * | 2008-02-20 | 2012-01-24 | Carbo Ceramics, Inc. | Method of logging a well using a thermal neutron absorbing material |
| US9514388B2 (en) * | 2008-08-12 | 2016-12-06 | Halliburton Energy Services, Inc. | Systems and methods employing cooperative optimization-based dimensionality reduction |
| CA2701109C (en) * | 2008-08-26 | 2015-06-16 | Halliburton Energy Services, Inc. | Method and system of processing gamma count rate decay curves using neural networks |
| WO2010123494A1 (en) | 2009-04-21 | 2010-10-28 | Halliburton Energy Services, Inc. | System and method of predicting gas saturation of a formation using neural networks |
| JP2011107648A (en) * | 2009-11-20 | 2011-06-02 | Fujifilm Corp | Lens unit |
| US8626447B2 (en) * | 2010-09-13 | 2014-01-07 | Chevron U.S.A. Inc. | System and method for sweet zone identification in shale gas reservoirs |
| US8648309B2 (en) | 2010-10-04 | 2014-02-11 | Carbo Ceramics Inc. | Spectral identification of proppant in subterranean fracture zones |
| EP2707572A1 (en) | 2011-06-24 | 2014-03-19 | Halliburton Energy Services, Inc. | Apparatus and methods of analysis of pipe and annulus in a wellbore |
| US8805615B2 (en) | 2011-09-08 | 2014-08-12 | Carbo Ceramics Inc. | Lithology and borehole condition independent methods for locating tagged proppant in induced subterranean formation fractures |
| US9038715B2 (en) | 2012-05-01 | 2015-05-26 | Carbo Ceramics | Use of PNC tools to determine the depth and relative location of proppant in fractures and the near borehole region |
| US9383473B2 (en) | 2012-06-26 | 2016-07-05 | Exxonmobil Upstream Research Company | Method for cement evaluation with neutron logs |
| US20140025301A1 (en) * | 2012-07-20 | 2014-01-23 | Bruce H. Storm, Jr. | Determination of subsurface properties of a well |
| US9022140B2 (en) | 2012-10-31 | 2015-05-05 | Resource Energy Solutions Inc. | Methods and systems for improved drilling operations using real-time and historical drilling data |
| GB2528191B (en) * | 2013-03-27 | 2019-12-04 | Logined Bv | Automatic geosteering and evolutionary algorithm for use with same |
| US20160231461A1 (en) * | 2013-12-19 | 2016-08-11 | Halliburton Energy Services, Inc. | Nuclear magnetic resonance (nmr) porosity integration in a probabilistic multi-log interpretation methodology |
| EP3052970A1 (en) | 2013-12-19 | 2016-08-10 | Halliburton Energy Services, Inc. | Pore size classification in subterranean formations based on nuclear magnetic resonance (nmr) relaxation distributions |
| AU2014384679B2 (en) * | 2014-02-26 | 2017-01-12 | Halliburton Energy Services, Inc. | Protein-based fibrous bridging material and process and system for treating a wellbore |
| US9501740B2 (en) | 2014-06-03 | 2016-11-22 | Saudi Arabian Oil Company | Predicting well markers from artificial neural-network-predicted lithostratigraphic facies |
| US10242312B2 (en) | 2014-06-06 | 2019-03-26 | Quantico Energy Solutions, Llc. | Synthetic logging for reservoir stimulation |
| US10677052B2 (en) * | 2014-06-06 | 2020-06-09 | Quantico Energy Solutions Llc | Real-time synthetic logging for optimization of drilling, steering, and stimulation |
| BR112017010684B1 (en) | 2014-12-29 | 2022-01-25 | Halliburton Energy Services, Inc | Cross-sensor linearization methods |
| US11531874B2 (en) | 2015-11-06 | 2022-12-20 | Google Llc | Regularizing machine learning models |
| WO2017197283A1 (en) | 2016-05-13 | 2017-11-16 | Carbo Ceramics Inc. | Capture gamma ray spectroscopy for analyzing gravel-packs, frac-packs and cement |
| WO2018057035A1 (en) * | 2016-09-26 | 2018-03-29 | Halliburton Energy Services, Inc. | Neutron porosity log casing thickness corrections |
| US9863895B1 (en) * | 2017-02-22 | 2018-01-09 | Saudi Arabian Oil Company | Systems and methods for monitoring casing cement integrity |
| WO2019089490A1 (en) * | 2017-10-30 | 2019-05-09 | Schlumberger Technology Corporation | System and method for automatic well log depth matching |
| CN109165737B (en) * | 2018-08-29 | 2020-09-01 | 电子科技大学 | Porosity prediction method based on conditional random field and BP neural network |
| CN109653730B (en) * | 2018-12-12 | 2021-12-14 | 中法渤海地质服务有限公司 | Underground perforation well section depth calibration method for drill rod stratum test operation |
| WO2021221519A1 (en) * | 2020-04-29 | 2021-11-04 | Sultan Qaboos University | Method of identifying hydrocarbon rich zones |
| WO2023004392A1 (en) * | 2021-07-21 | 2023-01-26 | Schlumberger Technology Corporation | Propagation of petrophysical properties to wells in a field |
| US20230314652A1 (en) * | 2022-03-31 | 2023-10-05 | Halliburton Energy Services, Inc. | Pulsed Neutron Informed Machine Learning Techniques To Determine Porosity And Lithology |
Family Cites Families (77)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3802259A (en) | 1970-11-27 | 1974-04-09 | Marathon Oil Co | Well logging method |
| US3946226A (en) | 1973-01-10 | 1976-03-23 | Texaco Inc. | Well logging method and apparatus |
| US4293933A (en) | 1975-03-17 | 1981-10-06 | Schlumberger Technology Corporation | Well logging apparatus and method: synthetic logs and synthetic seismograms with extrapolated reflector dip from log measurements |
| US4055763A (en) | 1975-03-31 | 1977-10-25 | Schlumberger Technology Corporation | Neutron characteristic and spectroscopy logging methods and apparatus |
| US3975157A (en) | 1975-07-21 | 1976-08-17 | Phillips Petroleum Company | Geochemical exploration using isoprenoids |
| US4122339A (en) | 1977-04-20 | 1978-10-24 | Texaco Inc. | Earth formation pulsed neutron porosity logging system utilizing epithermal neutron and inelastic scattering gamma ray detectors |
| US4122340A (en) | 1977-04-20 | 1978-10-24 | Texaco Inc. | Pulsed neutron porosity logging system |
| US4239965A (en) | 1979-03-05 | 1980-12-16 | Dresser Industries, Inc. | Method and apparatus for neutron induced gamma ray logging for direct porosity identification |
| US4297575A (en) | 1979-08-13 | 1981-10-27 | Halliburton Company | Simultaneous gamma ray measurement of formation bulk density and casing thickness |
| US4430567A (en) | 1981-01-22 | 1984-02-07 | Dresser Industries, Inc. | Method and apparatus for neutron induced gamma ray logging for direct porosity identification |
| FR2520882A1 (en) | 1982-02-02 | 1983-08-05 | Schlumberger Prospection | PROCESS FOR THE PRODUCTION OF A CHARACTERISTIC REGISTRATION IN PARTICULAR OF THE FACITIES OF GEOLOGICAL FORMATIONS CROSSED BY A SURVEY |
| US4605854A (en) | 1984-07-16 | 1986-08-12 | Halliburton Company | Measurement of formation porosity using fast neutron spectroscopy |
| US4656354A (en) | 1985-04-10 | 1987-04-07 | Dresser Industries, Inc. | Method for induced gamma ray logging |
| US4645926A (en) | 1985-04-10 | 1987-02-24 | Dresser Industries, Inc. | Method for induced gamma ray logging |
| US4617825A (en) | 1985-09-12 | 1986-10-21 | Halliburton Company | Well logging analysis methods for use in complex lithology reservoirs |
| US4926488A (en) | 1987-07-09 | 1990-05-15 | International Business Machines Corporation | Normalization of speech by adaptive labelling |
| US4912655A (en) | 1988-12-14 | 1990-03-27 | Gte Laboratories Incorporated | Adjusting neural networks |
| US5875284A (en) | 1990-03-12 | 1999-02-23 | Fujitsu Limited | Neuro-fuzzy-integrated data processing system |
| US5112126A (en) | 1990-07-27 | 1992-05-12 | Chevron Research & Technology Company | Apparatuses and methods for making geophysical measurements useful in determining the deflection of the vertical |
| JPH0489998A (en) | 1990-08-02 | 1992-03-24 | Nippon Telegr & Teleph Corp <Ntt> | Instruction device of propelling direction of small bore pipe |
| US5189415A (en) | 1990-11-09 | 1993-02-23 | Japan National Oil Corporation | Receiving apparatus |
| EP0513652A2 (en) | 1991-05-10 | 1992-11-19 | Siemens Aktiengesellschaft | Method for modelling similarity function using neural network |
| US5235185A (en) | 1992-01-09 | 1993-08-10 | Schlumberger Technology Corporation | Formation sigma measurement from thermal neutron detection |
| US5251286A (en) * | 1992-03-16 | 1993-10-05 | Texaco, Inc. | Method for estimating formation permeability from wireline logs using neural networks |
| US5353637A (en) | 1992-06-09 | 1994-10-11 | Plumb Richard A | Methods and apparatus for borehole measurement of formation stress |
| US5469404A (en) | 1992-11-12 | 1995-11-21 | Barber; Harold P. | Method and apparatus for seismic exploration |
| JP3335240B2 (en) | 1993-02-02 | 2002-10-15 | 富士写真フイルム株式会社 | Image processing condition setting method and apparatus |
| US5465321A (en) | 1993-04-07 | 1995-11-07 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | Hidden markov models for fault detection in dynamic systems |
| US5751915A (en) | 1993-07-13 | 1998-05-12 | Werbos; Paul J. | Elastic fuzzy logic system |
| US5444619A (en) | 1993-09-27 | 1995-08-22 | Schlumberger Technology Corporation | System and method of predicting reservoir properties |
| US5374823A (en) | 1993-10-28 | 1994-12-20 | Computalog U.S.A., Inc. | Pulsed neutron decay tool for measuring gamma radiation energy spectra for fast neutron inelastic collisions and thermal neutron capture events |
| US20020177954A1 (en) | 1994-03-17 | 2002-11-28 | Vail William Banning | Processing formation resistivity measurements obtained from within a cased well used to quantitatively determine the amount of oil and gas present |
| US5608215A (en) | 1994-09-16 | 1997-03-04 | Schlumberger Technology Corporation | Method and apparatus for determining density of earth formations |
| US5525797A (en) | 1994-10-21 | 1996-06-11 | Gas Research Institute | Formation density tool for use in cased and open holes |
| CA2165017C (en) | 1994-12-12 | 2006-07-11 | Macmillan M. Wisler | Drilling system with downhole apparatus for transforming multiple dowhole sensor measurements into parameters of interest and for causing the drilling direction to change in response thereto |
| US5828981A (en) * | 1995-05-11 | 1998-10-27 | Texaco Inc. | Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks |
| FR2738920B1 (en) | 1995-09-19 | 1997-11-14 | Elf Aquitaine | METHOD FOR AUTOMATIC SEISMIC FACIAL RECOGNITION |
| US5608214A (en) | 1995-10-30 | 1997-03-04 | Protechnics International, Inc. | Gamma ray spectral tool for well logging |
| WO1997044743A1 (en) | 1996-05-23 | 1997-11-27 | Siemens Aktiengesellschaft | Process for optimizing fuzzy rules using a computer |
| US5862513A (en) | 1996-11-01 | 1999-01-19 | Western Atlas International, Inc. | Systems and methods for forward modeling of well logging tool responses |
| US5915253A (en) * | 1996-12-13 | 1999-06-22 | Novell, Inc. | Method and system for implementing objects in a storage system |
| DE19703964C1 (en) | 1997-02-03 | 1998-10-15 | Siemens Ag | Process for transforming a fuzzy logic used to simulate a technical process into a neural network |
| DE19703965C1 (en) | 1997-02-03 | 1999-05-12 | Siemens Ag | Process for transforming a fuzzy logic used to simulate a technical process into a neural network |
| US5870690A (en) | 1997-02-05 | 1999-02-09 | Western Atlas International, Inc. | Joint inversion processing method for resistivity and acoustic well log data |
| US5900627A (en) | 1997-06-19 | 1999-05-04 | Computalog Research, Inc. | Formation density measurement utilizing pulse neutrons |
| WO1999001550A1 (en) | 1997-07-03 | 1999-01-14 | Dana-Farber Cancer Institute | A method for detection of alterations in msh5 |
| US5848379A (en) | 1997-07-11 | 1998-12-08 | Exxon Production Research Company | Method for characterizing subsurface petrophysical properties using linear shape attributes |
| JPH1185719A (en) | 1997-09-03 | 1999-03-30 | Matsushita Electric Ind Co Ltd | Parameter estimation device |
| US6466893B1 (en) | 1997-09-29 | 2002-10-15 | Fisher Controls International, Inc. | Statistical determination of estimates of process control loop parameters |
| US6044327A (en) | 1997-11-13 | 2000-03-28 | Dresser Industries, Inc. | Method for quantifying the lithologic composition of formations surrounding earth boreholes |
| US6140816A (en) | 1997-12-12 | 2000-10-31 | Schlumberger Technology Corporation | Method of determining the permeability of sedimentary strata |
| US6192352B1 (en) | 1998-02-20 | 2001-02-20 | Tennessee Valley Authority | Artificial neural network and fuzzy logic based boiler tube leak detection systems |
| US6150655A (en) | 1998-03-06 | 2000-11-21 | Computalog Research, Inc. | Inferential measurement of photoelectric absorption cross-section of geologic formations from neutron-induced, gamma-ray spectroscopy |
| US6207953B1 (en) | 1998-04-24 | 2001-03-27 | Robert D. Wilson | Apparatus and methods for determining gas saturation and porosity of a formation penetrated by a gas filled or liquid filled borehole |
| GB9904101D0 (en) | 1998-06-09 | 1999-04-14 | Geco As | Subsurface structure identification method |
| US6216134B1 (en) | 1998-06-25 | 2001-04-10 | Microsoft Corporation | Method and system for visualization of clusters and classifications |
| US6236942B1 (en) | 1998-09-15 | 2001-05-22 | Scientific Prediction Incorporated | System and method for delineating spatially dependent objects, such as hydrocarbon accumulations from seismic data |
| FR2788135B1 (en) | 1998-12-30 | 2001-03-23 | Schlumberger Services Petrol | METHOD FOR OBTAINING A DEVELOPED TWO-DIMENSIONAL IMAGE OF THE WALL OF A WELL |
| US6748369B2 (en) | 1999-06-21 | 2004-06-08 | General Electric Company | Method and system for automated property valuation |
| US6295504B1 (en) | 1999-10-25 | 2001-09-25 | Halliburton Energy Services, Inc. | Multi-resolution graph-based clustering |
| US6374185B1 (en) | 2000-02-18 | 2002-04-16 | Rdsp I, L.P. | Method for generating an estimate of lithological characteristics of a region of the earth's subsurface |
| US6560540B2 (en) | 2000-09-29 | 2003-05-06 | Exxonmobil Upstream Research Company | Method for mapping seismic attributes using neural networks |
| US6477469B2 (en) | 2001-01-08 | 2002-11-05 | Halliburton Energy Services, Inc. | Coarse-to-fine self-organizing map for automatic electrofacies ordering |
| US6789620B2 (en) | 2001-02-16 | 2004-09-14 | Halliburton Energy Services, Inc. | Downhole sensing and flow control utilizing neural networks |
| US6615211B2 (en) | 2001-03-19 | 2003-09-02 | International Business Machines Corporation | System and methods for using continuous optimization for ordering categorical data sets |
| US20020188424A1 (en) | 2001-04-20 | 2002-12-12 | Grinstein Georges G. | Method and system for data analysis |
| US6711522B2 (en) | 2001-04-25 | 2004-03-23 | Fujitsu Limited | Data analysis apparatus, data analysis method, and computer products |
| US7058763B2 (en) | 2001-05-04 | 2006-06-06 | Lucent Technologies Inc. | File system for caching web proxies |
| US20020178150A1 (en) | 2001-05-12 | 2002-11-28 | X-Mine | Analysis mechanism for genetic data |
| US20040019427A1 (en) | 2002-07-29 | 2004-01-29 | Halliburton Energy Services, Inc. | Method for determining parameters of earth formations surrounding a well bore using neural network inversion |
| US7114565B2 (en) | 2002-07-30 | 2006-10-03 | Baker Hughes Incorporated | Measurement-while-drilling assembly using real-time toolface oriented measurements |
| US6928367B2 (en) | 2002-09-27 | 2005-08-09 | Veritas Dgc Inc. | Reservoir fracture characterization |
| US8374974B2 (en) * | 2003-01-06 | 2013-02-12 | Halliburton Energy Services, Inc. | Neural network training data selection using memory reduced cluster analysis for field model development |
| US7814036B2 (en) * | 2003-06-19 | 2010-10-12 | Haliburton Energy Services, Inc. | Processing well logging data with neural network |
| US7280987B2 (en) | 2004-03-26 | 2007-10-09 | Halliburton Energy Services, Inc. | Genetic algorithm based selection of neural network ensemble for processing well logging data |
| US7613665B2 (en) | 2005-06-24 | 2009-11-03 | Halliburton Energy Services, Inc. | Ensembles of neural networks with different input sets |
| US7587373B2 (en) | 2005-06-24 | 2009-09-08 | Halliburton Energy Services, Inc. | Neural network based well log synthesis with reduced usage of radioisotopic sources |
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2005
- 2005-11-09 US US11/270,284 patent/US7587373B2/en active Active
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2006
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- 2006-06-26 WO PCT/US2006/025029 patent/WO2007002693A2/en active Application Filing
- 2006-06-26 CA CA2604738A patent/CA2604738C/en not_active Expired - Fee Related
- 2006-06-26 BR BRPI0611579-9A patent/BRPI0611579A2/en not_active IP Right Cessation
- 2006-06-26 GB GB0723890A patent/GB2441463B/en not_active Expired - Fee Related
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| GB0723890D0 (en) | 2008-01-23 |
| CA2604738C (en) | 2011-11-15 |
| WO2007002693A8 (en) | 2007-03-22 |
| BRPI0611579A2 (en) | 2011-02-22 |
| GB2441463B (en) | 2011-04-20 |
| WO2007002693A2 (en) | 2007-01-04 |
| US7587373B2 (en) | 2009-09-08 |
| US20070011115A1 (en) | 2007-01-11 |
| AU2006261707B2 (en) | 2010-02-25 |
| GB2441463A (en) | 2008-03-05 |
| WO2007002693A3 (en) | 2007-05-10 |
| AU2006261707A1 (en) | 2007-01-04 |
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