Data mining/analysis
This paper describes a data-driven well-management strategy that optimizes condensate recovery while preserving well productivity.
This paper explores the evolving role of the digital petroleum engineer, examines the core technologies they use, assesses the challenges they face, and projects future industry trends.
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.
-
There is often an assumption that big data, together with machine learning, will solve whatever problems asset-heavy industries such as oil and gas face. This is not the case; big data alone isn’t enough. We need something else to solve these problems, and the answer lies in the world of physics. -
SponsoredTo optimize decision-making, minimize risk, and create value, oil and gas companies can turn to liberated, contextualized data. For exploration or drilling, liberated, contextualized data can help the upstream industry make trustworthy decisions that save time and costs. This paper explains how.
-
SponsoredFor surveying, exploration, analytics, and a whole host of processes, liberated, contextualized data tailored to the environments of E&P subsurface will empower confidence, speed, reliability, agility, and most importantly, innovation. This is how Aker BP is doing it.
-
If design A yields the same 90-day production at 10% lower cost in a series of wells than design B wells, is design A the better one? Using pressure-based fracture measurements, the separability of variables between two completion designs can be evaluated.
-
For the upstream industry, where improvement in efficiency or production can drive significant financial results, there is no question that the size of the digital prize is huge. So are the challenges.
-
As part of the deal, Pertamina is moving all of its petrotechnical applications to the iEnergy cloud service, which is run by Halliburton arm Landmark.
-
The provider of subscription-based analytics services for the North American oil and gas sector continues its streak of purchasing data-focused firms.
-
The data-driven maintenance program incorporates riser condition, usage, and fatigue analysis with a risk-based inspection process.
-
SPE is planning a series on petroleum data analytics at its Houston Training Center. The series will kick off with Week One: Subsurface Analytics on 24–28 February and will be led by University of West Virginia Professor of Petroleum and Natural Gas Engineering Shahab Mohaghegh.
-
This paper investigates the most important independent variables, including petrophysics and completion parameters, to estimate ultimate recovery with a machine-learning algorithm. A novel machine-learning model based on random forest regression is introduced to predict estimated ultimate recovery.
