well spacing

This paper describes an auto-adaptive workflow that leverages a complex interplay between machine learning, physics of fluid flow, and a gradient-free algorithm to enhance the solution of well-placement problems.

This paper addresses the difficulty in adjusting late-stage production in waterflooded reservoirs and proposes an integrated well-network-design mode for CO₂ enhanced oil recovery and storage.

This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively.

This paper discusses cases from the North Sea and offshore California in which high-fidelity pressure and dynamics measurements, combined with high-speed telemetry, helped overcome complex geotechnical challenges.

This paper presents an efficient mathematical optimization method for well placement that maximizes contact with the productive zones for the best locations in the reservoir.

This work proposes a method to interpret far-field strain-change and pressure data to quantify fracture connectivity and properties at the cluster level.

his paper investigates the challenges faced in the development of mature and tight fields, primarily resulting from reservoir depletion, high operational costs, and uncertainty in reserves volumetric calculations.

This paper proposes a method to radically revise the well-path-generation process to reach the vision of planning a well in one day with high quality, relying on the collection of experience-based constraints from each discipline to generate possible alternatives.

This paper assesses the potential of augmented depletion development in four US plays: Bakken, Eagle Ford, Midland, and the Anadarko Basin.

This paper’s focus is a case study of an Eagle Ford refracturing project in which a range of completion designs were trialed with an approach using offset sealed wellbore pressure monitoring and fiber-optic strain.