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11.发明申请公开(公告)号：US20200096663A1
公开(公告)日：2020-03-26
申请号：US16612320
申请日：2018-04-23
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Sushil Shetty , Qiwei Zhan , Lin Liang , Austin Boyd , Smaine Zeroug , Vanessa Simoes , Fabio Cesar Canesin
Abstract: A method for determining properties of a laminated formation traversed by a well or wellbore employs measured sonic data, resistivity data, and density data for an interval-of-interest within the well or wellbore. A formation model that describe properties of the laminated formation at the interval-of-interest is derived from the measured sonic data, resistivity data, and density data for the interval-of-interest. The formation model represents the laminated formation at the interval-of-interest as first and second zones of different first and second rock types. The formation model is used to derive simulated sonic data, resistivity data, and density data for the interval-of-interest. The measured sonic data, resistivity data, and density data for the interval-of-interest and the simulated sonic data, resistivity data, and density data for the interval-of-interest are used to refine the formation model and determine properties of the formation at the interval-of-interest. The properties of the formation may be a radial profile for porosity, a radial profile for water saturation, a radial profile for gas saturation, radial profile of oil saturation, and radial profiles for pore shapes for the first and second zones (or rock types).
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公开(公告)号：US20180058211A1
公开(公告)日：2018-03-01
申请号：US15690306
申请日：2017-08-30
Applicant: Schlumberger Technology Corporation
Inventor： Lin Liang , Aria Abubakar , Tarek M. Habashy
CPC classification number: E21B49/00 , E21B44/00 , G01V1/282 , G01V1/306 , G01V1/50 , G01V3/26 , G01V3/38 , G01V11/00 , G01V2200/16 , G01V2210/614 , G01V2210/6163 , G01V2210/6167 , G01V2210/6169 , G01V2210/6244 , G01V2210/6246 , G01V2210/6248
Abstract: A method includes acquiring measurement values from at least two different types of downhole tools disposed in a portion of a bore in a formation; selecting formation parameters for joint inversion; building a near-bore fluid flow model of at least a portion of the formation that includes at least the portion of the bore; simulating fluid flow based at least in part on the near-bore fluid flow model and the selected formation parameters to generate simulated measurement values; comparing the acquired measurement values and the simulated measurement values; based at least in part on the comparing, revising at least one of the selected formation parameters to generate revised formation parameters and simulating fluid flow based at least in part on the near-bore fluid flow model and the revised formation parameters to generate revised simulated measurement values; and outputting at least the revised formation parameters to characterize the formation.
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公开(公告)号：US20250116791A1
公开(公告)日：2025-04-10
申请号：US18910162
申请日：2024-10-09
Applicant: Schlumberger Technology Corporation
Inventor： Gurami Keretchashvili , Ting Lei , Lin Liang
IPC: G01V1/50
Abstract: Embodiments presented provide for a classification of sonic data. In one aspect, visual features of sonic data are used to classify the sonic data and provide a quality control mechanism to ensure that a researcher understands the quality of the data calculations. In one or more embodiments, the method can obtain the raw sonic data from field measurements. The field measurements can pertain to downhole geological features.
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公开(公告)号：US11774622B2
公开(公告)日：2023-10-03
申请号：US16761471
申请日：2018-11-06
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Lalitha Venkataramanan , Lin Liang , Vasileios-Marios Gkortsas , Khaled Hadj-Sassi , Albina Mutina , Tarek Habashy
Abstract: A method, computer program product, and computing system for receiving downhole logging data for a porous media. A pore size distribution index may be estimated based upon, at least in part, nuclear magnetic resonance data (NMR) from the downhole logging data of the porous media. A relative permeability and capillary pressure curve may be generated with a feasible region of solutions based upon, at least in part, the pore size distribution index.
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公开(公告)号：US11531138B2
公开(公告)日：2022-12-20
申请号：US17237473
申请日：2021-04-22
Applicant: Schlumberger Technology Corporation
Abstract: Processes and systems for correlating well log data sets from well logging passes within a well bore. In some embodiments, a process for well log depth matching can include normalizing a first well log from a first logging pass obtained within a well bore and a second well log from a second logging pass obtained within the well bore, performing a pre-shift, performing feature picking to identify one or more features along the second well log, performing normalized cross-correlation based optimization between the first well log and the second well log to match the one or more features along the second well log to the same one or more features of the first well log and generating a shift table for depth shifting the one or more features of the second well log and the first well log.
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Patent Agency Ranking
公开(公告)号：US20220146705A1
公开(公告)日：2022-05-12
申请号：US17593092
申请日：2020-03-11
Applicant: Schlumberger Technology Corporation
Inventor： Vasileios-Marios Gkortsas , Lin Liang
Abstract: Facies of a formation are classified from data charactering properties of a portion of the formation as a function of depth, wherein the number of facies is determined automatically in an unsupervised manner without human input. In one embodiment, a layer-based methodology is provided that performs facies classification based on layer-based properties which are determined from well log data obtained from a plurality of different well logging tools. In another embodiment, a depth-based methodology is provided that performs facies classification based on well log data obtained depth-by-depth from a plurality of different well logging tools. The number of facies can be determined automatically without human input, for example using the Bayesian Information Criterion or a method which determines the optimal number of clusters based on the repeatability of the clustering results. In embodiments, the facies classification can be performed using the Gaussian mixture model (GMM) method.
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17.发明申请公开(公告)号：US20170371072A1
公开(公告)日：2017-12-28
申请号：US15544187
申请日：2016-01-25
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： Sushil Shetty , Lin Liang , Tarek M. Habashy , Vanessa Simoes , Austin Boyd , Bikash K. Sinha , Smaine Zeroug
CPC classification number: G01V99/005 , G01N15/088 , G01V11/00 , G01V2210/1429 , G01V2210/622
Abstract: A method for determining properties of a formation traversed by a well or wellbore employs measured sonic data, resistivity data, and density data for an interval-of-interest within the well or wellbore. A formation model that describe properties of the formation at the interval-of-interest is derived from the measured sonic data, resistivity data, and density data for the interval-of-interest. The formation model is used to derive simulated sonic data, resistivity data, and density data for the interval-of-interest. The measured sonic data, resistivity data, and density data for the interval-of-interest and the simulated sonic data, resistivity data, and density data for the interval-of-interest are used to refine the formation model and determine properties of the formation at the interval-of-interest. The properties of the formation may be a radial profile for porosity, a radial profile for water saturation, a radial profile for gas saturation, a radial profile of oil saturation, and a radial profile for pore aspect ratio.
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公开(公告)号：US12291963B2
公开(公告)日：2025-05-06
申请号：US17310988
申请日：2020-03-10
Applicant: Schlumberger Technology Corporation
Inventor： Chang-Yu Hou , Lin Liang , Lalitha Venkataramanan , Harish Baban Datir , Austin Boyd , Vasileios-Marios Gkortsas
Abstract: Methods and systems are provided characterizing a formation traversed by a wellbore, wherein the formation includes at least a flushed zone and an uninvaded zone, which involve obtaining well log data based on plurality of different well log measurements of the formation at multiple depths in the wellbore. The well log data is used by a computational model that solves for a set of petrophysical parameters that characterize a portion of the formation corresponding to the multiple depths in the wellbore, wherein the set of petrophysical parameters include a cementation exponent, a saturation exponent, and a flushed zone water resistivity. The solved-for set of petrophysical parameters can be used to determine a value of water saturation of the uninvaded zone for the portion of the formation corresponding to the multiple depths in the wellbore.
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公开(公告)号：US20250012184A1
公开(公告)日：2025-01-09
申请号：US18709883
申请日：2022-11-16
Applicant: Schlumberger Technology Corporation
Inventor： Ting Lei , Daniel Al Choboq , Josselin Kherroubi , Lin Liang , Romain Prioul , Gurami Keretchashvili , Pontus Loviken
Abstract: A general-purpose workflow for automatic borehole sonic data classification to identify data into different physical categories and logging conditions, which are traditionally manually evaluated. The workflow uses machine learning techniques and physical knowledge for data classification, including pre-processing the high-dimensional high-quality dispersion modes extracted using a recently developed physical-driven ML enabled approach.
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公开(公告)号：US20240418896A1
公开(公告)日：2024-12-19
申请号：US18815460
申请日：2024-08-26
Applicant: Schlumberger Technology Corporation
Abstract: The subject disclosure relates to the interpretation of borehole sonic data using machine learning. In one example of a method in accordance with aspects of the instant disclosure, borehole sonic data is received, and machine learning is used to interpret the borehole sonic data.
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