Integration of chemofacies and rock mechanical properties using machine learning algorithms: Implications for geomechanics and hydraulic fracture stimulations in paleozoic formations, Saudi Arabia

Maaruf Hussain, Abduljamiu Amao, Khalid Al-Ramadan, Sunday Olatunji, Ardiansyah Negara

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The knowledge of rock mechanical properties is critical to reducing drilling risk and maximizing well and reservoir productivity. Rock chemical composition, their spatial distribution, and porosity significantly influenced these properties. However, low porosity characterized unconventional reservoirs as such, geochemical properties considerably control their mechanical behavior. In this study, we used chemostratigraphy as a correlation tool to separate strata in highly homogenous formations where other traditional stratigraphic methods failed. In addition, we integrated the chemofacies output and reduced Young's modulus to outline predictable associations between facies and mechanical properties. Thus, providing better understanding of lithofacies-controlled changes in rock strength that are useful inputs for geomechanical models and completions stimulations.

Original languageEnglish
Title of host publicationSociety of Petroleum Engineers - SPE Annual Technical Conference and Exhibition 2021, ATCE 2021
PublisherSociety of Petroleum Engineers (SPE)
ISBN (Electronic)9781613997864
DOIs
StatePublished - 2021
EventSPE Annual Technical Conference and Exhibition 2021, ATCE 2021 - Dubai, United Arab Emirates
Duration: 21 Sep 202123 Sep 2021

Publication series

NameProceedings - SPE Annual Technical Conference and Exhibition
Volume2021-September

Conference

ConferenceSPE Annual Technical Conference and Exhibition 2021, ATCE 2021
Country/TerritoryUnited Arab Emirates
CityDubai
Period21/09/2123/09/21

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