Authors : Praveen Kumar Mishra; Dr. Manish Kumar

Volume/Issue : Volume 9 - 2024, Issue 11 - November

Google Scholar : https://shorturl.at/iO3Ot

Scribd : https://shorturl.at/1xZdM

DOI : https://doi.org/10.38124/ijisrt/IJISRT24NOV818

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This paper examines how AI is transforming petroleum exploration and development, addressing current applications and future directions. Machine learning is being used to enhance tasks like identifying rock types, reconstructing logging curves, and estimating reservoir parameters, showing promise in improving data processing and interpretation. In seismic analysis, computer vision helps with identifying initial seismic signals and detecting faults. Deep learning and optimization techniques are applied in reservoir engineering, enabling real-time waterflooding optimization and production forecasting for oil and gas. Data mining is also enhancing drilling, completion, and facility operations, leading to smarter equipment and integrated software. Looking ahead, AI in petroleum is poised to advance with intelligent production tools, automated data processing, and specialized software platforms. Future innovations are expected in digital basin modeling, fast imaging logging tools, advanced seismic systems, smart drilling and fracturing technologies, and real-time monitoring of injection and production zones.

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