DSDE: In Practice

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…

This paper presents a comprehensive technical review of applications of distributed acoustic sensing.

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.

The site survey and inspection of an offshore gas platform in UAE waters was executed entirely from an onshore remote operations center without sending personnel offshore.

The authors of this paper describe a solution using machine-learning techniques to predict sandstone distribution and, to some extent, automate the process of optimizing well placement.

The objective of this study was to establish an efficient optimization work flow to improve vertical and areal sweep in a sour-gas injection operation, thereby maximizing recovery under operation constraints.

This paper introduces a method using a Bayesian network to aggregate trends detected in time-series data with events identified by natural language processing to improve the accuracy and robustness of kick and lost-circulation detection.