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公开(公告)号：US20210389487A1
公开(公告)日：2021-12-16
申请号：US17445956
申请日：2021-08-26
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose , Bikash K. Sinha
Abstract: A method for determining a shear slowness of a subterranean formation includes receiving waveforms data acquired by receivers in an acoustic measurement tool in response to energy emitted by at least one dipole source. The waveforms are processed to extract a formation flexural acoustic mode and a tool flexural acoustic mode. The processing includes transforming the time domain waveforms to frequency domain waveforms, processing the frequency domain waveforms with a Capon algorithm to compute a two-dimensional spectrum over a chosen range of group slowness and phase slowness values; and processing the two-dimensional spectrum to extract the multi-mode slowness dispersion. The method further includes selecting a plurality of slowness-frequency pairs from the formation flexural mode of the extracted multi-mode dispersion wherein each slowness-frequency pair comprises a slowness value at a corresponding frequency and processing the selected slowness frequency pairs to compute the shear slowness of the subterranean formation.
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公开(公告)号：US20160209538A1
公开(公告)日：2016-07-21
申请号：US14908530
申请日：2014-08-05
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Pu Wang , Sandip Bose
IPC: G01V1/48
CPC classification number: G01V1/48
Abstract: An apparatus is provided for extracting slowness dispersion characteristics of sonic wave forms in broadband acoustic waves received by multiple sensors including means to digitize the sonic wave forms to form discrete time wave forms and converting the discrete time wave forms into frequency domain wave forms and means to divide a processing band of the wave forms into frequency sub-bands. For each sub-band approximating a family of candidate dispersion curves for multiple modes, parameterizing each of the curves by phase and group slowness, and forming a frequency dependent over-complete dictionary of basis elements, each corresponding to a pair of phase and group slownesses. In addition, forming multiple measurement vectors from the frequency domain data and implementing a sparse Bayesian learning (SBL) algorithm on the vectors with a block sparse signal model and outputting the results. Also, a means for generating a fmal dispersion curve.
Abstract translation: 提供了一种用于提取由多个传感器接收的宽带声波中的声波形式的慢度色散特性的装置，包括将声波形式数字化以形成离散时间波形并将离散时间波形转换成频域波形的装置， 将波形的处理频带划分为频率子带。 对于每个子带，近似多个模式的候选色散曲线系列，通过相位和组慢度对每个曲线进行参数化，并形成基本元素的频率依赖过完整字典，每个子带对应于一对相位和群体慢度 。 另外，从频域数据形成多个测量向量，并对具有块稀疏信号模型的向量实现稀疏贝叶斯学习（SBL）算法并输出结果。 另外，产生最终色散曲线的方法。
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公开(公告)号：US10809400B2
公开(公告)日：2020-10-20
申请号：US15331958
申请日：2016-10-24
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose , Bikash Sinha
Abstract: A technique includes receiving data acquired by an acoustic measurement tool in a well, where the data represents multiple acoustic modes, including a first order formation flexural acoustic mode and a higher order formation flexural acoustic mode. The technique includes processing the data to identify the higher order formation flexural acoustic mode; and determining a shear slowness based at least in part on slowness values that are associated with the identified higher order formation flexural acoustic mode.
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公开(公告)号：US11119237B2
公开(公告)日：2021-09-14
申请号：US16093640
申请日：2017-04-13
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Pu Wang , Sandip Bose , Bikash Kumar Sinha , Ting Lei
Abstract: Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging-while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time-varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.
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公开(公告)号：US10228484B2
公开(公告)日：2019-03-12
申请号：US15337824
申请日：2016-10-28
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Pu Wang , Vikas Jain , Lalitha Venkataramanan
IPC: G01V3/38 , G01N24/08 , E21B47/12 , G06N7/00 , G06F17/18 , G01V3/32 , G06N99/00 , E21B49/00 , G01R33/44
Abstract: Methods and systems for characterizing a subterranean formation using nuclear magnetic resonance (NMR) measurements are described herein. One method includes locating a downhole logging tool in a wellbore that traverses the subterranean formation, and performing NMR measurements to obtain NMR data for a region of the subterranean formation. The NMR data is processed by employing sparse Bayesian learning (SBL) to determine a multi-dimensional property distribution of the NMR data (e.g., T1-T2, D-T2, and D-T1-T2 distributions). The sparse Bayesian learning can utilize Bayesian inference that involves a prior over a vector of basis coefficients governed by a set of hyperparameters, one associated with each basis coefficient, whose most probable values are iteratively estimated from the NMR data. The sparse Bayesian learning can achieve sparsity because posterior distributions of many of such basis coefficients are sharply peaked around zero.
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Patent Agency Ranking
公开(公告)号：US20170115414A1
公开(公告)日：2017-04-27
申请号：US15331958
申请日：2016-10-24
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose , Bikash Sinha
CPC classification number: G01V1/306 , G01V1/284 , G01V1/303 , G01V1/50 , G01V2200/16 , G01V2210/42 , G01V2210/43 , G01V2210/47 , G01V2210/6222 , G01V2210/626
Abstract: A technique includes receiving data acquired by an acoustic measurement tool in a well, where the data represents multiple acoustic modes, including a first order formation flexural acoustic mode and a higher order formation flexural acoustic mode. The technique includes processing the data to identify the higher order formation flexural acoustic mode; and determining a shear slowness based at least in part on slowness values that are associated with the identified higher order formation flexural acoustic mode.
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公开(公告)号：US11835673B2
公开(公告)日：2023-12-05
申请号：US17473555
申请日：2021-09-13
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose , Bikash Kumar Sinha , Ting Lei
CPC classification number: G01V1/50 , G01V1/284 , G01V2200/16 , G01V2210/47 , G01V2210/626
Abstract: Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging-while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time-varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.
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公开(公告)号：US20220075087A1
公开(公告)日：2022-03-10
申请号：US17473555
申请日：2021-09-13
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose , Bikash Kumar Sinha , Ting Lei
Abstract: Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging-while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time-varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.
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公开(公告)号：US09927543B2
公开(公告)日：2018-03-27
申请号：US14908530
申请日：2014-08-05
Applicant: Schlumberger Technology Corporation
Inventor： Pu Wang , Sandip Bose
IPC: G01V1/48
CPC classification number: G01V1/48
Abstract: An apparatus is provided for extracting slowness dispersion characteristics of sonic wave forms in broadband acoustic waves received by multiple sensors including means to digitize the sonic wave forms to form discrete time wave forms and converting the discrete time wave forms into frequency domain wave forms and means to divide a processing band of the wave forms into frequency sub-bands. For each sub-band approximating a family of candidate dispersion curves for multiple modes, parameterizing each of the curves by phase and group slowness, and forming a frequency dependent over-complete dictionary of basis elements, each corresponding to a pair of phase and group slownesses. In addition, forming multiple measurement vectors from the frequency domain data and implementing a sparse Bayesian learning (SBL) algorithm on the vectors with a block sparse signal model and outputting the results. Also, a means for generating a final dispersion curve.
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公开(公告)号：US20170123098A1
公开(公告)日：2017-05-04
申请号：US15337824
申请日：2016-10-28
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Pu Wang , Vikas Jain , Lalitha Venkataramanan
CPC classification number: G01V3/38 , E21B49/00 , G01N24/081 , G01R33/448 , G01V3/32 , G06N7/005 , G06N99/005
Abstract: Methods and systems for characterizing a subterranean formation using nuclear magnetic resonance (NMR) measurements are described herein. One method includes locating a downhole logging tool in a wellbore that traverses the subterranean formation, and performing NMR measurements to obtain NMR data for a region of the subterranean formation. The NMR data is processed by employing sparse Bayesian learning (SBL) to determine a multi-dimensional property distribution of the NMR data (e.g., T1-T2, D-T2, and D-T1-T2 distributions). The sparse Bayesian learning can utilize Bayesian inference that involves a prior over a vector of basis coefficients governed by a set of hyperparameters, one associated with each basis coefficient, whose most probable values are iteratively estimated from the NMR data. The sparse Bayesian learning can achieve sparsity because posterior distributions of many of such basis coefficients are sharply peaked around zero.
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