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This paper presents an AI-driven workflow for transforming legacy and modern well log data processing through automation. The focus includes raster log digitization, quality control (QC), auto-splicing of multiple log runs, and the prediction of missing curves using advanced AI and Generative AI models. The objective is to reduce manual effort, improve data reliability, and accelerate subsurface interpretation workflows across large-scale datasets.
This paper explores the application of Artificial Intelligence (AI) and Generative AI (Gen AI) to enhance production optimization and predictive maintenance in oil and gas fields. Focusing on field examples from the USA and India, the study demonstrates how AI-driven strategies can reduce downtime, improve operational efficiency, and support data-driven decision-making in upstream and midstream operations.
Drake AI uses OCR and deep learning to digitize raster well logs, extracting curves and text into structured formats. This enables fast, accurate analysis and seamless integration with modern geoscience platforms.
Drake AI automates well log splicing using AI to detect overlaps, align depth scales, and merge segments accurately. This ensures consistent, high-quality logs for faster interpretation and reduces manual workload.
Drake AI uses AI and ML models trained on regional log data to predict missing curves with high accuracy, enabling better reservoir characterization and decision-making even when original logs are incomplete or absent.
Drake AI uses deep learning and CNNs to reconstruct missing seismic frequencies by learning spatial patterns and spectral relationships, enhancing resolution and improving subsurface imaging accuracy.
Drake AI uses advanced AI/ML algorithms to analyze real-time and historical production data, uncover hidden patterns, and optimize variables like flow rates and pressures, boosting output while reducing costs and downtime.
Drake AI uses OCR with advanced AI/ML to extract structured data from unstructured well and field reports, enabling fast, accurate digitization for easier analysis, integration, and decision-making.
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