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1.发明申请公开(公告)号：US20220179121A1
公开(公告)日：2022-06-09
申请号：US17438340
申请日：2020-03-09
Applicant: Schlumberger Technology Corporation
Inventor： Paul Ryan Craddock , Lalitha Venkataramanan , Prakhar Srivastava , Harish Baban Datir
Abstract: Methods and systems are provided to learn and apply a mapping function from data representing concentrations of atomic elements in a geological formation (or other data corresponding thereto) to mineral component concentrations in the geological formation (and/or from mineral component concentrations to reconstructed elemental concentrations in the geological formation). The mapping function can be derived from a trained neural network (such as an autoencoder). The output of the mapping function can be used to determine estimates of one or more formation properties, such as formation matrix density, formation porosity, matrix Sigma, formation saturation, other formation property, or combinations thereof.
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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：US20240345273A1
公开(公告)日：2024-10-17
申请号：US18580196
申请日：2022-07-21
Applicant: Schlumberger Technology Corporation
CPC classification number: G01V1/306 , G01V1/50 , G01V2210/6244 , G01V2210/6246
Abstract: Embodiments of the disclosure provide a method to propagate a set of petrophysical measurements in at least one well to a well not having a full set of petrophysical measurements. The method includes identifying a first data set for a first well. The method also includes identifying a second data set for a second well. Using a mapping derived from the first well, the petrophysical property for measurement A can be derived for the second well from measurement B of the second well.
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公开(公告)号：US20250052924A1
公开(公告)日：2025-02-13
申请号：US18723648
申请日：2023-01-05
Applicant: Schlumberger Technology Corporation
Inventor： Paul Ryan Craddock , Jeffrey Miles , Lalitha Venkataramanan , Harish Baban Datir , Prakhar Srivastava
Abstract: Rock properties of a geological formation may be determined using data representing elemental concentration within the geological formation. For example, the data representing the elemental concentration within the geological formation may be provided as input to a mapping function. The mapping function may capture nonlinear relationships among the concentrations of measurable elements in geological rock formation(s) and certain rock properties of said rock formation(s). Embodiments of the present disclosure are directed to techniques that improve determinations of rock properties of geological formations.
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Patent Agency Ranking
公开(公告)号：US20220082014A1
公开(公告)日：2022-03-17
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 to 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：US09772425B2
公开(公告)日：2017-09-26
申请号：US13804333
申请日：2013-03-14
Applicant: Schlumberger Technology Corporation
Inventor： David Nanlung Dangfa , Ilaria De Santo , Iftikhar Khattak , Harish Baban Datir
CPC classification number: G01V3/32 , G01N24/081 , Y02A90/344
Abstract: A nuclear magnetic resonance (NMR) measurement, at two or more depths of investigation, of a subsurface formation containing formation water and a mud filtrate from a water-base mud is obtained, and the mud filtrate is distinguished from the formation water. A NMR logging tool is disposed in a wellbore penetrating the formation containing the mud filtrate and the formation water and NMR measurements at different radial depths of investigation into the formation are made. The mud filtrate is distinguished from the formation water by determining the relative salinities of the mud filtrate and the formation water. The relative salinities are determined by comparing distribution relaxation times across different depths of investigation or by comparing logarithmic mean values across different depths of investigation.
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7.发明授权公开(公告)号：US11988802B2
公开(公告)日：2024-05-21
申请号：US17438340
申请日：2020-03-09
Applicant: Schlumberger Technology Corporation
Inventor： Paul Ryan Craddock , Lalitha Venkataramanan , Prakhar Srivastava , Harish Baban Datir
IPC: G01V5/10 , E21B49/00 , G01N33/24 , G06N3/04 , G06N3/045 , G06N3/08 , G06N3/084 , G06N3/088 , E21B49/02 , G06N3/082
CPC classification number: G01V5/101 , E21B49/00 , E21B49/005 , G01N33/24 , G06N3/045 , G06N3/08 , G06N3/084 , G06N3/088 , E21B49/02 , E21B2200/20 , E21B2200/22 , G06N3/082
Abstract: Methods and systems are provided to learn and apply a mapping function from data representing concentrations of atomic elements in a geological formation (or other data corresponding thereto) to mineral component concentrations in the geological formation (and/or from mineral component concentrations to reconstructed elemental concentrations in the geological formation). The mapping function can be derived from a trained neural network (such as an autoencoder). The output of the mapping function can be used to determine estimates of one or more formation properties, such as formation matrix density, formation porosity, matrix Sigma, formation saturation, other formation property, or combinations thereof.
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8.发明申请公开(公告)号：US20220187495A1
公开(公告)日：2022-06-16
申请号：US17310991
申请日：2020-03-11
Applicant: Schlumberger Technology Corporation
Inventor： Denise E. Freed , Harish Baban Datir , Peter Tilke , Oliver C. Mullins , Lalitha Venkataramanan , Sandip Bose
Abstract: Embodiments herein include a system and method for modeling and interpreting an evolution of fluids in an oilfield using artificial intelligence. Embodiments may include identifying, using at least one processor, one or more reservoir fluid dynamics processes or properties and generating a model for the one or more reservoir fluid dynamics processes or properties. Embodiments may include receiving, at the model, one or more parameter values corresponding to the one or more reservoir fluid dynamics processes or properties and displaying, at a graphical user interface, one or more results, based upon, at least in part, the model and the one or more parameter values.
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公开(公告)号：US20130271127A1
公开(公告)日：2013-10-17
申请号：US13804333
申请日：2013-03-14
Applicant: SCHLUMBERGER TECHNOLOGY CORPORATION
Inventor： David Nanlung Dangfa , Ilaria De Santo , Iftikhar Khattak , Harish Baban Datir
IPC: G01V3/32
CPC classification number: G01V3/32 , G01N24/081 , Y02A90/344
Abstract: A nuclear magnetic resonance (NMR) measurement, at two or more depths of investigation, of a subsurface formation containing formation water and a mud filtrate from a water-base mud is obtained, and the mud filtrate is distinguished from the formation water. A NMR logging tool is disposed in a wellbore penetrating the formation containing the mud filtrate and the formation water and NMR measurements at different radial depths of investigation into the formation are made. The mud filtrate is distinguished from the formation water by determining the relative salinities of the mud filtrate and the formation water. The relative salinities are determined by comparing distribution relaxation times across different depths of investigation or by comparing logarithmic mean values across different depths of investigation.
Abstract translation: 获得含有地层水的地下地层和来自水基泥浆的泥浆滤液的两个或更多个勘探深度的核磁共振（NMR）测量，泥浆滤液与地层水不同。 NMR测井工具设置在渗透含有泥浆滤液的地层的井眼中，并且在不同径向深度的地层中进行地层水和NMR测量。 通过确定泥浆滤液和地层水的相对盐度，泥浆滤液与地层水不同。 相对盐度通过比较不同深度的调查分布松弛时间或通过比较不同深度的对数平均值来确定。
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