artificial intelligence

End-To-End Petrophysical Operations with Agentic AI: A Horizontal Carbonate Reservoir Well Case Study from a Mature Onshore Field, Abu Dhabi

Abstract Petrophysical work follows a well from planning through drilling and into completion, and at each step it usually passes between different specialists, vendor software, and email threads. This paper describes an in-house agentic artificial-intelligence assistant that brings those steps together behind one inte...

Predicting Tomorrow's Failure Today: AI-Driven Time-To-Failure and Multivariable Deviation Analytics for Advancing Reliability and Production Excellence

Oil and gas facilities operate as interconnected systems. A change in one part of the plant can affect equipment reliability, process stability, production, energy use, and emissions elsewhere. Conventional surveillance relies on alarms, operating limits, inspections, and subject matter expertise. These safeguards re...

Reinventing the Upstream Control Room: An Agentic AI Approach to Early Deviation Detection and Remediation

Abstract The upstream control room is where production, injection, chemical, and emissions performance are monitored against target, and where operational deviations must be detected and resolved before they compound into lost output, avoidable emissions, or safety exposure. In practice, this task is hindered by four r...

Revolutionizing Reservoir Surveillance: A Deep Dive Into Virtual Well Testing Technology

Abstract This paper analyses a five-year implementation of an innovative Virtual Well Testing (VWT) technology for reservoir surveillance. VWT enables continuous, real-time insight into reservoir performance and well productivity. The tool utilizes the power of artificial intelligence, making it a live asset management...

Multi-Agent AI Framework to Reduce FEL-To-FID Cycle Time in Upstream Capital Projects

Abstract Front-End Loading (FEL) is the decisive value-shaping phase of upstream capital projects, yet it remains slow, sequential, and heavily dependent on scarce specialist expertise. This paper defines and validates an artificial-intelligence (AI) enabled, end-to-end capital project delivery framework that reduces c...

Centralized AI-Enabled Energy Performance Management Over Enterprise IIoT Platform

Abstract Energy is one of the largest controllable operating costs and a primary source of greenhouse-gas emissions in upstream oil and gas operations. Yet in most large assets, energy information remains fragmented across electrical meters, supervisory control systems, historians, spreadsheets, and monthly reports. Th...

Petroleum Target Explorer (PTX-AIM): A Rigorously Validated Machine Learning Framework for TOC Prediction in Frontier Basins, a Case Study from the Kolmani River-2 Well, Gongola Basin, Upper Benue Trough, Nigeria

Abstract Objectives/Scope The Kolmani River discovery confirmed a working petroleum system in Nigeria's Gongola Basin (Upper Benue Trough), but too few wells and sampled intervals exist for conventional Total Organic Carbon (TOC) prediction to be reliable. We present PTX-AIM (Petroleum Target Explorer – Artificial Inte...

Autonomous Refinery Intelligence Architecture

Abstract Refinery decisions often require evidence that is distributed across plant historians, maintenance systems, work permits, incident records, management-of-change registers, audit actions, shift logs, engineering documents, and workforce-compliance records. Conventional search or dashboard solutions generally ad...

Physics-Guided AI–Numerical Simulation for Sand Production Prediction and Completion Optimization

Abstract Sand production is a nonlinear, path-dependent, and strongly coupled process controlled by reservoir depletion, effective-stress redistribution, near-wellbore stress concentration, elastoplastic failure, damage accumulation, grain debonding, hydraulic detachment, erosion, and particulate transport. Its occurre...

Identification and Localization of Remaining Mobile Oil in Mature Fields Using Integrated Physics-Based and AI/ML Workflow: A Case Study

Abstract Identification and localization of remaining mobile oil are fundamental components of mature-field reservoir management. This task becomes increasingly challenging when large portfolios contain numerous fields, reservoirs, fault blocks, and producing intervals with varying levels of data completeness and subsu...

From Data to Decision: A Field-Validated AI-Assisted Production Intelligence Framework for Opportunity Identification, Artificial Lift Optimization, and Surveillance in the Indus Basin

Abstract Objectives/Scope The increasing complexity of mature oil, gas, and condensate assets has expanded surveillance data volumes while making rapid identification of high-value production opportunities increasingly difficult. Conventional workflows rely on fragmented datasets, manual interpretation, and reactive as...

Legal Issues and Challenges in Disclosure of Information in Breach of Contract by Artificial Intelligence Service Providers