Research on intelligent decision support systems for oil and gas exploration based on machine learning.

ABSTRACT: The process of extracting oil and gas via borehole drilling is largely dependent on subsurface structures, and thus, well log analysis is a major concern for economic feasibility. Well logs are essential for understanding the geology below the earth's surface, which allows for the estimation of the available hydrocarbon resources. The incompleteness of these logs, on the other hand, is a major hindrance to downstream analysis success. This study, however, addresses the above challenges and presents a deep Long-Short Term Memory (LSTM) model specialized using a new hyperparameter tuning algorithm. There is an evidence gap that we try to fill: well log prediction using LSTM has not been extensively documented, particularly on reconstruction of missing data. In order to remedy this, we develo

SUBMITTER: Wang Z 

PROVIDER: S-EPMC11620558 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature