公开(公告)号：US12124480B2

公开(公告)日：2024-10-22

申请号：US18060136

申请日：2022-11-30

Applicant: Schlumberger Technology Corporation

Inventor： Rishabh Gupta ,  Dinakar Gollapinni ,  Tharunya Danabal

IPC: G06F16/00 ,  G06F16/21 ,  G06F16/28

CPC classification number: G06F16/285 ,  G06F16/211

Abstract: A dataset is received from a data source. A first plurality of string similarities between metadata of the dataset with a plurality of attributes of a plurality of data classes in a target schema are calculated to determine a data class. A set of relationships are assigned to the data class based on relationships between the plurality of data classes in the target schema. A second plurality of string similarities between a plurality of attributes of the dataset and a plurality of attributes of the data class are calculated. Datatypes and measurement units are assigned to the plurality of attributes of the dataset according to the second plurality of string similarities. A source schema is generated based on the data class, the set of relationships, the plurality of attributes of the data class and the measurement units.

公开(公告)号：US20240230938A1

公开(公告)日：2024-07-11

申请号：US18537958

申请日：2023-12-13

Applicant: Schlumberger Technology Corporation

Inventor： Tharunya Danabal ,  Rishabh Gupta ,  Svapanil Patel

IPC: G01V1/30

CPC classification number: G01V1/301 ,  G01V2210/512 ,  G01V2210/514

Abstract: A method includes obtaining a digital seismic file, obtaining a digital seismic file, and performing autodetection of parameters of the digital seismic file. The method further includes extracting seismic data from the digital seismic file according to the parameters to generate normalized seismic data. The method further includes scanning the normalized seismic data to obtain metadata that includes geographic file boundaries and mapping the normalized seismic data to a parent virtual survey based at least in part on the geographic file boundaries being in a geographic region of a parent virtual survey. The method additionally includes storing, in a target store, the normalized seismic data and metadata, the normalized seismic data in a stored relationship with the parent virtual survey in the target store.

公开(公告)号：US20240184009A1

公开(公告)日：2024-06-06

申请号：US18556432

申请日：2022-04-20

Applicant: Schlumberger Technology Corporation

Inventor： Rishabh Gupta ,  Svapanil Patel ,  Udit Sinha

IPC: G01V1/36

CPC classification number: G01V1/362 ,  G01V2210/512 ,  G01V2210/514

Abstract: A method includes obtaining a digital seismic file, performing autodetection of parameters of the digital seismic file, and registering the parameters of the digital seismic file with the digital seismic file. Performing autodetection comprises a computer processor, repetitively until a candidate template successfully extracts the parameters, selecting a target candidate template, attempting extraction of a binary header using the target candidate template, attempting extraction of a trace header using the target candidate template, attempting extraction of the plurality of parameters when the target candidate template extracts the binary header and the trace header, and moving to a next target candidate template when extraction of the plurality of headers is unsuccessful.

公开(公告)号：US12099154B2

公开(公告)日：2024-09-24

申请号：US18556432

申请日：2022-04-20

Applicant: Schlumberger Technology Corporation

Inventor： Rishabh Gupta ,  Svapanil Patel ,  Udit Sinha

IPC: G01V1/36

CPC classification number: G01V1/362 ,  G01V2210/512 ,  G01V2210/514

Abstract: A method includes obtaining a digital seismic file, performing autodetection of parameters of the digital seismic file, and registering the parameters of the digital seismic file with the digital seismic file. Performing autodetection comprises a computer processor, repetitively until a candidate template successfully extracts the parameters, selecting a target candidate template, attempting extraction of a binary header using the target candidate template, attempting extraction of a trace header using the target candidate template, attempting extraction of the plurality of parameters when the target candidate template extracts the binary header and the trace header, and moving to a next target candidate template when extraction of the plurality of headers is unsuccessful.

公开(公告)号：US20240304016A1

公开(公告)日：2024-09-12

申请号：US18260526

申请日：2022-01-07

Applicant: Schlumberger Technology Corporation

Inventor： Rishabh Gupta ,  Swapnil Patel ,  Udit Sinha

IPC: G06V30/413 ,  G06F16/35 ,  G06V30/19 ,  G06V30/412 ,  G06V30/414 ,  G06V30/42

CPC classification number: G06V30/413 ,  G06F16/353 ,  G06V30/19147 ,  G06V30/412 ,  G06V30/414 ,  G06V30/42 ,  G06V2201/10

Abstract: A method involves extracting, from a file comprising an unstructured oilfield document, terms, calculating term frequency inverse document frequency (TF-IDF) of the terms to generate an input vector, execute a document content classification model on the input vector to generate a document content classification of unstructured oilfield document, and extract table information from a table in the unstructured oilfield document. The method further involves storing, with the file in storage, the document content classification and the table information.

公开(公告)号：US20240176803A1

公开(公告)日：2024-05-30

申请号：US18060136

申请日：2022-11-30

Applicant: Schlumberger Technology Corporation

Inventor： Rishabh Gupta ,  Dinakar Gollapinni ,  Tharunya Danabal

IPC: G06F16/28 ,  G06F16/21

CPC classification number: G06F16/285 ,  G06F16/211

Abstract: A dataset is received from a data source. A first plurality of string similarities between metadata of the dataset with a plurality of attributes of a plurality of data classes in a target schema are calculated to determine a data class. A set of relationships are assigned to the data class based on relationships between the plurality of data classes in the target schema. A second plurality of string similarities between a plurality of attributes of the dataset and a plurality of attributes of the data class are calculated. Datatypes and measurement units are assigned to the plurality of attributes of the dataset according to the second plurality of string similarities. A source schema is generated based on the data class, the set of relationships, the plurality of attributes of the data class and the measurement units.