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Applications of AI in oil and gas projects towards sustainable development: a systematic literature review
Oil and gas construction projects are critical for meeting global demand for fossil fuels, but
they also present unique risks and challenges that require innovative construction …
they also present unique risks and challenges that require innovative construction …
The Fourier transform infrared spectroscopy (FTIR) analysis for the clay mineralogy studies in a clastic reservoir
The complete characteristics knowledge of clay minerals is necessary in the evaluation
studies of hydrocarbon reservoirs. Ten samples taken from two wells in a heterogeneous …
studies of hydrocarbon reservoirs. Ten samples taken from two wells in a heterogeneous …
Reservoir quality prediction of gas-bearing carbonate sediments in the Qadirpur field: Insights from advanced machine learning approaches of SOM and cluster …
The detailed reservoir characterization was examined for the Central Indus Basin (CIB),
Pakistan, across Qadirpur Field Eocene rock units. Various petrophysical parameters were …
Pakistan, across Qadirpur Field Eocene rock units. Various petrophysical parameters were …
Reservoir characterization through comprehensive modeling of elastic logs prediction in heterogeneous rocks using unsupervised clustering and class-based …
Geophysical reservoir characterization is a significant task in the oil and gas industry and
elastic logs prediction of subsurface formations is a fundamental aspect of this process …
elastic logs prediction of subsurface formations is a fundamental aspect of this process …
A core logging, machine learning and geostatistical modeling interactive approach for subsurface imaging of lenticular geobodies in a clastic depositional system, SE …
Facies models are essential tools for imaging subsurface geobodies and for reducing
exploration and development risks efficiently. The Lower Goru Formation is one of the …
exploration and development risks efficiently. The Lower Goru Formation is one of the …
Machine learning-A novel approach of well logs similarity based on synchronization measures to predict shear sonic logs
This study proposes a novel approach to predict missing shear sonic log responses more
precisely and accurately using similarity patterns of various wells with similar geophysical …
precisely and accurately using similarity patterns of various wells with similar geophysical …
A robust strategy of geophysical logging for predicting payable lithofacies to forecast sweet spots using digital intelligence paradigms in a heterogeneous gas field
The most crucial elements in the oil and gas sector are predicting subsurface lithofacies
utilizing geophysical logs for reservoir characterization and sweet spot assessment …
utilizing geophysical logs for reservoir characterization and sweet spot assessment …
[HTML][HTML] Classification of reservoir quality using unsupervised machine learning and cluster analysis: Example from Kadanwari gas field, SE Pakistan
Understanding geological variance in a proved reservoir requires accurate as well as exact
characterization of lithological facies. In the Kadanwari gas field, machine learning (ML) …
characterization of lithological facies. In the Kadanwari gas field, machine learning (ML) …
An ensemble-based strategy for robust predictive volcanic rock ty** efficiency on a global-scale: a novel workflow driven by big data analytics
Laboratory measurements, paleontological data, and well-logs are often used to conduct
mineralogical and chemical analyses to classify rock samples. Employing digital intelligence …
mineralogical and chemical analyses to classify rock samples. Employing digital intelligence …
[HTML][HTML] Application of machine learning for lithofacies prediction and cluster analysis approach to identify rock type
Nowadays, there are significant issues in the classification of lithofacies and the
identification of rock types in particular. Zamzama gas field demonstrates the complex nature …
identification of rock types in particular. Zamzama gas field demonstrates the complex nature …