Comparative evaluation of multi-basin production performance and application of spatio-temporal models for unconventional oil and gas production prediction

Marshal E Wigwe, Edwyn S Bougre, Marshall Watson, Alberto Giussani

Research output: Contribution to journalArticlepeer-review

Abstract

Modern data analytic techniques, statistical and machine-learning algorithms have received widespread applications for solving oil and gas problems. As we face problems of parent-child well interactions, well spacing, and depletion concerns, it becomes necessary to model the effect of geology, completion design, and well parameters on production using models that can capture both spatial and temporal variability of the covariates on the response variable. We accomplish this using a well-formulated spatio-temporal (ST) model. In this paper, we present a multi-basin study of production performance evaluation and applications of ST models for oil and gas data. We analyzed dataset from 10,077 horizontal wells from 2008 to 2019 in five unconventional formations in the USA: Bakken, Marcellus, Eagleford, Wolfcamp, and Bone Spring formations. We evaluated well production performance and performance of new completions over time. Results show increased productivity of oil and gas since 2008. Al
Original languageEnglish
Pages (from-to)3091–3110
JournalJournal of Petroleum Exploration and Production Technology
DOIs
StatePublished - Jul 24 2020

Fingerprint Dive into the research topics of 'Comparative evaluation of multi-basin production performance and application of spatio-temporal models for unconventional oil and gas production prediction'. Together they form a unique fingerprint.

Cite this