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Well spacing optimization is one of the more important considerations in unconventional field development.

To continue to advance optimization in new-well completions, to cost-effectively restimulate existing wells, and to enhance recovery, will require capacity for laboratory studies and field trial programs and implementation of a range of analytical methodologies.

This work describes a heuristic approach combining mathematical modeling and associated data-driven work flows for estimating reservoir-pressure surfaces through space and time using measured data.

Digital transformation supported by data analytics and artificial intelligence can be the differentiator that allows the upstream industry to persist in the next 100 years, providing a unique foundation for innovation to enhance general public awareness and life quality.

The authors examine methods of adopting an aggressive approach to optimizing stimulation design to lower the break-even level of operations and evaluate the results.

This paper reviews the IOR/EOR technologies currently being applied to unconventional oil reservoirs.

While sand control in production wells catches much attention, water-injection wells also are subject to sand-control problems triggered by water hammer, cross flow, and backflow. Newly developed screens for water-injection wells have been demonstrated with promising results.

The authors present a novel data-driven tool for fast fracture identification in post-stack seismic data sets.

Seismic imaging provides vital tools for the exploration of potential hydrocarbon reserves and subsequent production-planning activities. The acquisition of high-resolution, regularly sampled seismic data may be hindered by physical or financial constraints.

This paper discusses a probabilistic flux and erosion model and work flow that extend the ability to estimate inflow through sand screens on a foot-by-foot basis along the wellbore using the well's completion details, production rate, and reservoir and bottomhole flowing pressures.