[Free GPT-4]
The total organic carbon content (TOC) is the most important parameter when determining
the source rock quality. At present, there are two main types of TOC well logging calculation …
the source rock quality. At present, there are two main types of TOC well logging calculation …
Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields
The analysis of total organic carbon (TOC) contents is an important activity in exploring
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
Forming a new small sample deep learning model to predict total organic carbon content by combining unsupervised learning with semisupervised learning
The total organic carbon (TOC) content is a parameter that is directly used to evaluate the
hydrocarbon generation capacity of a reservoir. For a reservoir, accurately calculating TOC …
hydrocarbon generation capacity of a reservoir. For a reservoir, accurately calculating TOC …
Estimation of oil recovery factor for water drive sandy reservoirs through applications of artificial intelligence
Hydrocarbon reserve evaluation is the major concern for all oil and gas operating
companies. Nowadays, the estimation of oil recovery factor (RF) could be achieved through …
companies. Nowadays, the estimation of oil recovery factor (RF) could be achieved through …
Data-driven modeling approach for pore pressure gradient prediction while drilling from drilling parameters
Real-time prediction of the formation pressure gradient is critical mainly for drilling
operations. It can enhance the quality of decisions taken and the economics of drilling …
operations. It can enhance the quality of decisions taken and the economics of drilling …