Fracturing/pressure pumping
This paper describes an approach to creating a digital, interconnected workspace that aligns sensor data with operational context to place the completions engineer back into a central role.
This paper demonstrates how the integration of multiphysics downhole imaging with machine-learning techniques provides a significant advance in perforation-erosion analysis.
This paper presents a workflow that leverages a multiagent conversational system to integrate data, analytics, and domain expertise for improved completion strategies.
-
Two US test sites have fractured hot, dry rock with plans to create a network of fractures for water heating. They will soon find out if the fractures worked as expected. -
This article presents a new data-driven analysis to locate low-frequency seismic sources, referred to as near-infrasound or infrasound sources. Combining these infrasound signals with microseismicity signals allows for better characterization and monitoring of the stimulated reservoir volume.
-
Fracturing hot rock to create a geological water-heating system is like fracturing an oil well, but for a different purpose, so is proppant really necessary?
-
When confronted by extremely hot wells drilled into hard rock, engineers start looking for new tools and then ask, is there a cheaper option?
-
From refracturing old wells to ones that don’t have to be fractured at all, notable producers argue that experiments are paying off.
-
The SPE Hydraulic Fracturing Technology Conference and Exhibition is being held 31 January–2 February in The Woodlands, Texas.
-
ProPetro will provide committed services for a 3-year period to an undisclosed Permian Basin operator.
-
This paper presents a numerical simulation work flow, with emphasis on hydraulic fracture simulation, that optimizes well spacing and completion design simultaneously.
-
Recent studies have reignited the question of whether US oil and gas companies are ignoring the opportunity to refracture large swaths of maturing assets.
-
The authors discuss the development of a deep-learning model to identify errors in simulation-based performance prediction in unconventional reservoirs.
