Schlumberger Technology Corporation

Services Petroliers Schlumberger

Geoquest Systems B.v.

Sergey Doronichev

Velizar Vesselinov

Jose Celaya Galvan

Carlos Boneti

Andrey Sergeevich Konchenko

Valerian Guillot

Emilien Dupont

Siau Ban Teh

Rod W Shampine

Bruce MacKay

Suhas Suresha

Vishakh Hegde

Xiaotong Suo

Markus Schlafli

Jared Bruns

Kim Swift

Salvador Ruiz-Esparza

Jared Krichko

Anthony Lichnewsky

Ewan Maxwell

Apoorva Dubey

Tong Zhang

A subsurface structure identification system includes one or more processors and a memory coupled to the one or more processors. The memory is encoded with instructions that when executed by the one or more processors cause the one or more processors to provide a convolutional neural network trained to identify a subsurface structure in an input migrated seismic volume, and to partition the input migrated seismic volume into multi-dimensional sub-volumes of seismic data. The instructions also cause the one or more processors to process each of the multi-dimensional sub-volumes of seismic data in the convolutional neural network, and identify the subsurface structure in the input migrated seismic volume based on a probability map of the input migrated seismic volume generated by the convolutional neural network.

System and method for identifying subsurface structures

A system can include a processor; memory operatively coupled to the processor; and processor-executable instructions stored in the memory to instruct the system to: receive a marker on a well log for a well in a geographic region; and iteratively propagate the marker automatically to a plurality of well logs for other wells in the geographic region.

Well log correlation and propagation system

Methods, apparatuses, and computer-readable media are set forth for visualizing and interacting with well production data in a three-dimensional or four-dimensional environment, e.g., using a volumetric well production display representation representing a well in an oilfield and including a plurality of display characteristics configured to display historical production data for the well over a time period.

Volumetric well production user interface components

A method including obtaining a first image of a geographical location and a physical object located therein. Pixels in the first image are assigned to corresponding points in a Cartesian coordinate system defined specifically for the first image. The resulting virtual map includes a virtual representation of the physical object, a set of Cartesian coordinates assigned to a set of pixels in the pixels, and a set of Cartesian rotation angles assigned to the set of pixels. A first transform is calculated that scales the Cartesian coordinate system to a physical scale of the geographical location. A data structure stored in a data repository is formed by applying the first transform to the virtual map. The data structure includes the set of pixels, a set of scaled Cartesian coordinates, the set of Cartesian rotation angles, and a physical scale virtual representation of the physical object.

Data structures for augmented reality planning of geographic locations

Computing system assessment of geological similarity of wells employing well-log data includes receiving logs with chronostratigraphic markers, and extracting signatures from the logs using the chronostratigraphic markers. A distance matrix is generated from the signatures using dynamic time warping. Using the distance matrix, a set of clusters are generated. The set of clusters are presented with an image.

Computing system assessment of geological similarity of wells employing well-log data

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Menlo Park, CA, United States of America

Sergey Doronichev