The Use of Machine Learning in Oil Well Petrophysics and Original Oil in Place Estimation: A Systematic Literature Review Approach

Machine learning is a form of artificial intelligence that applicable in all fields study. It incorporates many algorithms used carrying out various tasks such as classification, predictions, estimations, comparisons, approximations, optimization and selections. In estimating original oil place, which affords the explorationist foresight on total amount crude potentially reservoir. found to perform reserves estimation with speed accuracy where insufficient data are available. These among other attributes Learning motivated systematic literature review studies undertaken between 2010 2021 explore strengths limitations reported studies. industry, different types gathered from subsurface surface order know reservoir hydrocarbon potential. Sensorsare known be able collect these large quantity, analyse predict output.3127 articles related study were collated 4 databases after series inclusion exclusion criteria conducted articles, 104 journal met for review. Results reveal years under review, 2019 had greatest number (20 104) pertaining topic reviewed. 61% authors inadequate while 39 % under-performance algorithm. was also revealed machine applied predictions/forecasting industry than it solve problems, Artificial Neural Network (ANN) most technique. The opens another vista knowledge researchers navigate place petrophysics analysis. This emerging technology smart makes evaluation easy straightforward.