Abstract
Gamma-ray (GR) logging involves the measurement of natural formations' radioactivity, serving as a valuable tool for distinguishing various lithologies and correlating zones.A prevalent approach is to record GR data up to the surface through the casing while pulling out of the hole (POOH) using reservoir section logging tools.Although GR measurements are very helpful, they are seldom recorded in the top section.This study utilizes artificial intelligence (AI) techniques-specifically artificial neural network (ANN) and adaptive neurofuzzy inference system (ANFIS)-to predict real-time surface hole GR by leveraging drilling parameters and mud weight data.Training on datasets from six wells with a total of 2,100 data set yielded accurate predictions, with the ANN model slightly surpassing ANFIS in performance.The models were and assessed for accuracy using metrics such as root mean square error (RMSE), average absolute percentage error (AAPE), and correlation coefficient (R).These models offer substantial benefits by providing real-time GR data for analysis, thereby eliminating the necessity for post-drilling recordings.This advancement not only saves time and costs associated with logging but also enhances the efficiency of data-driven decision-making during drilling operations.
Original language | English |
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Title of host publication | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
Publisher | American Rock Mechanics Association (ARMA) |
ISBN (Electronic) | 9798331305086 |
DOIs | |
State | Published - 2024 |
Event | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 - Golden, United States Duration: 23 Jun 2024 → 26 Jun 2024 |
Publication series
Name | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
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Conference
Conference | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
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Country/Territory | United States |
City | Golden |
Period | 23/06/24 → 26/06/24 |
Bibliographical note
Publisher Copyright:Copyright 2024 ARMA, American Rock Mechanics Association.
ASJC Scopus subject areas
- Geochemistry and Petrology
- Geophysics