Landmark Graphics Corporation

Michael Charles Quintrell Treloar

Owen Edward Sutcliffe

Daniel James David Slidel

Andrew Davies

James Iain Scotchman

Mike Derek Simmons

A system is described for determining an analogue geological feature. The system may include a processor and a non-transitory computer-readable medium comprising instructions that are executable by the processor to cause the processor to perform various operations. The system may generate, by extracting parameter signatures for geological features, a database including parameters about geological features associated with parameter signatures. The system may receive data including parameters and a feature-type about a geological feature of interest. The system may generate a signature including values for a subset of the feature-of-interest parameters selected based on the geological feature of interest for the feature-of-interest using the data. The system may execute a comparison of the feature signature to the parameter signatures included in the database for identifying an analogue geological feature for the feature of interest. The system may output a subset of parameters for the analogue for use in subterranean exploration.

Geological database management using signatures for hydrocarbon exploration

A system for determining exploration potential ranking for petroleum plays according to some aspects receives geological survey data of a geographical area to be ranked for a future petroleum play. The system generates predicted values based on the geological survey data, each predicted value indicating a probability that a portion of the basin includes a first characteristic. A set of polygons that represent the basin may be generated based on the predicted values. Each polygon represents a contiguous portion of the basin that has a same predicted value. A basin is score is generated by: generating a score for each polygon using the predicted value; and aggregating the score of each polygon of the set of polygons into the basin score. The basin score is displayed for use displaying for use in determining an area in which drilling a wellbore would have a greater probability of success.

Determining exploration potential ranking for petroleum plays

A system includes a processor and a memory. The memory includes instructions that are executable by the processor to cause the processor to receive basin data of a target basin including an area of the target basin, a number of exploration wells in the target basin, and a number of discovery wells in the target basin. Additionally, the instructions are executable to cause the processor to provide the basin data as input to a trained machine-learning model to determine a predicted trajectory of exploration efficiency of the target basin. Further, the instructions are executable to cause the processor to, in response to providing the basin data as input to the trained machine-learning model, receive an output from the trained machine-learning model indicating the predicted trajectory of exploration efficiency in the target basin.

Facilitating hydrocarbon exploration by applying a machine-learning model to basin data

A system for analysis and display of hydrocarbon play information according to some aspects determines a probability of source rock occurrence according to source rock age based on a proven play concept. The system can also determine a relative probability of migration for hydrocarbons from a source rock of a proposed petroleum play concept to a reservoir. A relative probability of wellbore success for the proposed play concept can be determined at least in part based on these probabilities. The system can display the relative probability of wellbore success for the proposed play concept, either alone as part of a displayed inventory of proposed hydrocarbon play concepts. The system can produce accurate results that facilitate rapid play concept investigations for hydrocarbon exploration.

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Didcot, United Kingdom

Michael Charles Quintrell Treloar