DSDE: In Practice

Finding and producing crude and natural gas is far, far removed from the days of acting on a geologist’s hunch or a wildcatter’s gut feeling.

This paper describes an 18-month intensive continuous improvement process between an operator, a rig contractor, and bottomhole-assembly (BHA) service providers aimed at reducing BHAs per well in two Oklahoma rigs.

This paper presents the concept of a supervisory and advisory system dedicated to support the detection of abnormal events and to provide guidelines for fluid treatment.

This paper highlights a thermodynamic modeling approach used to determine the optimal depth for installation of a wax-inhibition tool.

The authors of this paper write that computationally coupled models enable swift, accurate, and engineered decision-making for optimal asset development.

This paper presents an approach to optimize the location of wellhead towers using an algorithm based on multiple parameters related to well cost.

The authors of this paper present an artificial-lift timing and selection work flow using a hybrid data-driven and physics-based approach that incorporates routinely available pressure/volume/temperature, rate, and pressure information.

Large methane emissions occur from a wide variety of oil and gas industry sites with no discernable patterns, thus requiring methods to monitor for these releases throughout the production chain. This paper describes a continuous monitoring system based on the Internet of Things using methane concentration sensors permanently deployed at facilities and connected to a…

The authors of this paper analyze a robust, well-distributed parent/child well data set using a combination of available empirical data and numerical simulation outputs to develop a predictive machine-learning model.

In this paper, example machine-learning models were trained using geologic, completion, and spacing parameters to predict production across the primary developed formations within the Midland Basin.