US 12,366,153 B2
Well construction equipment framework
Gregory Michael Skoff, Cambridge (GB); Crispin Chatar, Menlo Park, CA (US); Velizar Vesselinov, Sugar Land, TX (US); Cheolkyun Jeong, Sugar Land, TX (US); Fatma Mahfoudh, Cambridge (GB); Sergey Makarychev-Mikhailov, Cambridge (GB); Oleh Petryshak, Poltava (UA); Yezid Arevalo Romero, Katy, TX (US); Yingwei Yu, Katy, TX (US); and Georgia Kouyialis, New York, NY (US)
Assigned to Schlumberger Technology Corporation, Sugar Land, TX (US)
Filed by Schlumberger Technology Corporation, Sugar Land, TX (US)
Filed on Jul. 12, 2022, as Appl. No. 17/811,931.
Claims priority of provisional application 63/220,882, filed on Jul. 12, 2021.
Prior Publication US 2023/0017966 A1, Jan. 19, 2023
Int. Cl. E21B 44/00 (2006.01); E21B 7/04 (2006.01); G06F 16/2458 (2019.01); G06F 16/28 (2019.01)
CPC E21B 44/00 (2013.01) [E21B 7/04 (2013.01); G06F 16/2468 (2019.01); G06F 16/285 (2019.01); E21B 2200/20 (2020.05); E21B 2200/22 (2020.05)] 19 Claims
OG exemplary drawing
 
1. A method comprising:
receiving input for a drilling operation that utilizes a bottom hole assembly and drilling fluid;
generating a set of offset drilling operations using historical feature data and predicted feature data from one or more machine learning models based on at least a portion of the input, wherein the historical feature data is processed by computing feature distances;
performing an assessment of the set of offset drilling operations as characterized by feature distance-based similarity between the drilling operation and the set of offset drilling operations, wherein the feature distance-based similarity is determined by:
receiving a first selection of one or more pair-wise distance metrics of a set of data points within a multidimensional space plot via a graphical user interface (GUI), wherein each of the one or more pair-wise distance metrics corresponds to the drilling operation and one of the set of offset drilling operations;
receiving one or more weights associated with the one or more pair-wise distance metrics via the GUI;
generating one or more weighted pair-wise distance metrics based on the one or more pair-wise distance metrics and the one or more weights;
determining a similarity index for each of the one or more weights associated with the one or more pair-wise distance metrics; and
generating, based on the similarity index, at least one recommendation of an adjustment to a trajectory of the drilling operation by the bottom hole assembly and a flow of the drilling fluid;
outputting the at least one recommendation for selection via the GUI;
receiving at least one rating as feedback, via the GUI, to the at least one recommendation and training at least one of the one or more machine learning models based at least in part on the at least one rating;
receiving the selection of the at least one recommendation via the GUI; and
sending one or more commands to the bottom hole assembly in response to receiving the selection, wherein the one or more commands are configured to cause the bottom hole assembly to adjust the trajectory of the drilling operation or the flow of the drilling fluid according to the selection.