公开(公告)号：US12282462B2

公开(公告)日：2025-04-22

申请号：US18155133

申请日：2023-01-17

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli

IPC: G06F16/215 ,  G06F16/28 ,  G06F16/93

Abstract: A method includes identifying entities in a well record database comprising data representing a plurality of objects and attributes of the objects, determining a data gap for at least one attribute of an object of the objects in the well record database, identifying documents in a document database, wherein identifying the documents include determining that the documents are relevant to the object based at least in part on metadata of the documents, extracting values for the data gap from the documents using a machine learning model, determining a data gap filler by aggregating the extracted values, and inserting the data gap filler into the data gap in the well log database.

公开(公告)号：US11829399B1

公开(公告)日：2023-11-28

申请号：US17814383

申请日：2022-07-22

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli

IPC: G06F7/00 ,  G06F16/33 ,  G06V30/412 ,  G06F40/279 ,  G01V11/00 ,  G06V30/413

CPC classification number: G06F16/3347 ,  G01V11/002 ,  G06F40/279 ,  G06V30/412 ,  G06V30/413 ,  G06V2201/10

Abstract: Systems, computer-readable media, and methods are provided. Relevant documents related to a specific entity are identified based on document metadata. Text and associated spatial coordinates are extracted based on relevant document pages. Significant document entities and associated spatial locations are identified. Page ranking is based on the extracted text and the spatial coordinates, the significant document entities, and image vector representations of the pages. A deep learning language model that utilizes the text and the spatial coordinates, layout information of the document entities, and the image vector representations of the pages is used to extract the user-defined attributes from the relevant document pages. First attribute values associated with the user-defined attributes are aggregated from the pages of one of the relevant documents into a single record. Second attribute values associated with the user-defined attributes are aggregated across the relevant documents. Aggregated records, including a first and second attribute, are written to a database.

公开(公告)号：US20240153299A1

公开(公告)日：2024-05-09

申请号：US18548628

申请日：2022-03-01

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli ,  Karan Pathak

IPC: G06V30/416 ,  G06F40/106 ,  G06V30/146 ,  G06V30/16 ,  G06V30/19 ,  G06V30/414

CPC classification number: G06V30/416 ,  G06F40/106 ,  G06V30/1463 ,  G06V30/1475 ,  G06V30/16 ,  G06V30/19147 ,  G06V30/414 ,  G06V30/42

Abstract: A method involves detecting primary entities in a document, involving determining that a subset of the primary entities are associated with a first primary entity type, and determining a second primary entity type of one of the primary entities. The method further involves processing the primary entity of the second primary entity type to determine a secondary entity type of the primary entity. The secondary entity type is a subcategory of the second primary entity type. The method also involves hierarchically organizing the primary entities into a document layout structure that includes a top level and a child level. The top level is established by the first subset of primary entities based on the first primary entity type identifying the first subset as headings, and the child level is established by the primary entity based on the second primary entity type, the child level identifying the secondary entity type.

公开(公告)号：US20240086440A1

公开(公告)日：2024-03-14

申请号：US18519322

申请日：2023-11-27

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli

IPC: G06F16/33 ,  G01V11/00 ,  G06F40/279 ,  G06V30/412 ,  G06V30/413

CPC classification number: G06F16/3347 ,  G01V11/002 ,  G06F40/279 ,  G06V30/412 ,  G06V30/413 ,  G06V2201/10

Abstract: Systems, computer-readable media, and methods are provided. Relevant documents related to a specific entity are identified based on document metadata. Text and associated spatial coordinates are extracted based on relevant document pages. Significant document entities and associated spatial locations are identified. Page ranking is based on the extracted text and the spatial coordinates, the significant document entities, and image vector representations of the pages. A deep learning language model that utilizes the text and the spatial coordinates, layout information of the document entities, and the image vector representations of the pages is used to extract the user-defined attributes from the relevant document pages. First attribute values associated with the user-defined attributes are aggregated from the pages of one of the relevant documents into a single record. Second attribute values associated with the user-defined attributes are aggregated across the relevant documents. Aggregated records, including a first and second attribute, are written to a database.

公开(公告)号：US20250052147A1

公开(公告)日：2025-02-13

申请号：US18720793

申请日：2023-01-30

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Maurice Ringer ,  Purnaprajna Mangsuli ,  Vladimir Skvortsov

IPC: E21B47/12 ,  E21B44/02 ,  G06N20/00

Abstract: A method includes receiving historical well data comprising trajectories, performance data, and one or more drilling parameters for a plurality of wells, clustering at least a portion of the plurality of wells into a plurality of clusters based on the trajectories, using a machine learning model, receiving trajectory data for a subject well, identifying one of the clusters based on the trajectory data of the subject well, using the machine learning model, selecting one or more of the plurality of wells, or one or more sections thereof, in the cluster that was identified based on the performance data associated with the one or more of the plurality of wells or the portion thereof, and visualizing the selected one or more of the plurality of wells or one or more sections thereof.

公开(公告)号：US12147464B2

公开(公告)日：2024-11-19

申请号：US18519322

申请日：2023-11-27

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli

IPC: G06F7/00 ,  G01V11/00 ,  G06F16/33 ,  G06F40/279 ,  G06V30/412 ,  G06V30/413

Abstract: Systems, computer-readable media, and methods are provided. Relevant documents related to a specific entity are identified based on document metadata. Text and associated spatial coordinates are extracted based on relevant document pages. Significant document entities and associated spatial locations are identified. Page ranking is based on the extracted text and the spatial coordinates, the significant document entities, and image vector representations of the pages. A deep learning language model that utilizes the text and the spatial coordinates, layout information of the document entities, and the image vector representations of the pages is used to extract the user-defined attributes from the relevant document pages. First attribute values associated with the user-defined attributes are aggregated from the pages of one of the relevant documents into a single record. Second attribute values associated with the user-defined attributes are aggregated across the relevant documents. Aggregated records, including a first and second attribute, are written to a database.

公开(公告)号：US20240241868A1

公开(公告)日：2024-07-18

申请号：US18155133

申请日：2023-01-17

Applicant: Schlumberger Technology Corporation

Inventor： Prashanth Pillai ,  Purnaprajna Raghavendra Mangsuli

IPC: G06F16/215 ,  G06F16/28 ,  G06F16/93

CPC classification number: G06F16/215 ,  G06F16/287 ,  G06F16/93

Abstract: A method includes identifying entities in a well record database comprising data representing a plurality of objects and attributes of the objects, determining a data gap for at least one attribute of an object of the objects in the well record database, identifying documents in a document database, wherein identifying the documents include determining that the documents are relevant to the object based at least in part on metadata of the documents, extracting values for the data gap from the documents using a machine learning model, determining a data gap filler by aggregating the extracted values, and inserting the data gap filler into the data gap in the well log database.