Bandwidth of Nanotechnology in the Oil Field Widens
Nanotechnology has great potential to reduce cost, increase production, and even improve the sustainability of E&P operations. But, where do we stand in terms of potential vs. reality? And, is the industry ready and willing to use the technology?
Data-Driven Analytics Provide Novel Approach to Performance Diagnosis
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.
Artificial Intelligence Improves Seismic-Image Reconstruction
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.
Data-Driven Tool Uses Amplitude-Based Statistics To Identify Seismic Fractures
The authors present a novel data-driven tool for fast fracture identification in post-stack seismic data sets.
Emerson Accelerates Digital Transformation of Oil and Gas Industry With Cloud-Hosted Software Suite on Microsoft Azure
The engineering and technology company announced its entire exploration and production software suite is now available on the cloud, enabling oil and gas companies to take advantage of digital technologies securely and to model and optimize production better.
Natural Language Processing Enables Better Operational Risk Management
Equinor is working on a natural language processing tool that could combine data sources and help planners anticipate the issues that affect onsite operational safety.
Permian Space Race: Satellites Become Latest Tool for Competitive Shale Play
At least a half dozen energy data firms are offering satellite imaging of the 75,000-sq-mile oil field to provide intelligence to energy companies on activities including the appearance of drilling pads and hydraulic fracturing ponds and the movements of drilling rigs and crews across the Permian.
Parallel Simulation and Cloud Computing Can Optimize Large-Scale Field Development
The complete paper discusses a study in which the authors propose a joint field-development and well-control-optimization work flow using high-performance parallel simulation and commercial cloud computing.
Gazprom Neft Develops Supercomputer To Simulate Siberian and Arctic Fields
The Russian company has built a computing cluster in St. Petersburg designed to generate digital twins of oil fields. The new distributed-computing system is capable of processing more than 100 gigabits per second, speeding up the digital-modeling process five-fold.
Establishing a Drone Business With the FAA's Part 107 in Oil and Gas
Drones have entered the oil and gas domain as a more comprehensive method of inspection—providing not only a flexible and cost-effective way to conduct inspections but also a data-intensive structure for inspecting assets in a nondestructive manner.
Machine Learning Can Make Mooring Safer and More Cost Effective
Concern has been growing in the oil and gas industry about the high frequency of mooring line failures. While physical tension sensors can be difficult and costly to maintain, machine learning has shown to be a more-accurate and less-costly method for structural integrity assessment.
Data Mining Effective for Casing-Failure Prediction and Prevention
This paper is part of an ongoing effort to minimize the likelihood of failure using data-mining and machine-learning algorithms.
Big Data vs. Diverse Data: Confidential Databases Lack Performance Benchmarks
A study by a real-time monitoring company showed that many coiled-tubing strings are retired with a lot of life left in them. It suggested companies could lower costs by using pipe for a longer time and could benefit from multicompany studies showing how their decisions compare to the competition.
Computational Model Predicts Breakdown Pressures in Unconventional Plays
This paper presents a newly developed model to predict the breakdown pressures in cased and perforated wells.
Surface Drilling Data Can Help Optimize Fracture Treatment in Real Time
This paper presents a unique work flow that addresses in real time the challenges of perforation and fracture-treatment design while accounting for the lithologic and stress variability along the wellbore and its surroundings.
Digital Transformation Increases Value in an Omani Thermal EOR Asset
A thermal asset in Oman is characterized by a large-scale steam-drive/cyclic-steam-soak development project, underpinned by extensive data gathering.
Artificial Intelligence Can Reduce ESP Failures
Electrical-submersible-pump (ESP) technology predominates available artificial-lift options. The risk of ESP failures can be reduced greatly with the right combination of advanced technologies, such as combining artificial intelligence with a cloud-based autonomous surveillance system.
Machine Learning Optimizes Duvernay Shale-Well Performance
This paper discusses how machine learning by use of multiple linear regression and a neural network was used to optimize completions and well designs in the Duvernay shale.
ABS Unveils Guide for Using Smart Technology in Marine and Offshore Industries
The first set of notations of its kind helps owners and operators qualify and use smart functions to manage asset health and performance.
$1 Million Gift From ConocoPhillips Will Enhance Data Science Offerings at University of Houston
Demand is growing at the University of Houston and others from students who want to study data science; from researchers who produce, interpret, or otherwise work with reams of data; and from industry, which needs a data science-savvy workforce.
GHGSat Readies Launch of Second Emissions-Monitoring Satellite
The new satellite will build on the success of the company's demonstration satellite Claire, which has performed over 2,500 observations of oil and gas facilities as well as other natural and industrial sources of carbon dioxide and methane.
Integrating Geomechanical Data Optimizes Completions Design
This paper demonstrates how engineers can take advantage of their most-detailed completions and geomechanical data by identifying trends arising from past detailed treatment analyses.
Digital Transformation Pushes Companies To Rethink How They Work
With new digital platforms and technologies driving the industry in the near future, organizations are examining the ways in which their established work flows may help or hinder their ability to adopt and adapt.
Oil Companies Must Learn To Share
Like a fast-declining oil well, the value of propriety software is short-lived. Technological advances drive down the value of programs, many of which were never unique.
Machine-Learning Approach Identifies Wolfcamp Reservoirs
This paper discusses a project with the objective of leveraging prestack and poststack seismic data in order to reconstruct 3D images of thin, discontinuous, oil-filled packstone pay facies of the Upper and Lower Wolfcamp formation.
How To Find the Right Data System for Equipment Inspections
Inspection data management system software can help companies bolster their mechanical integrity programs, but choosing the wrong software can have a lasting impact on a company’s operations. So, what goes into finding the right software for your needs?
Companies Are Failing in Their Efforts To Become Data-Driven
Leading corporations seem to be failing in their efforts to become data-driven. This is a central and alarming finding of NewVantage Partners’ 2019 Big Data and AI Executive Survey.
As Expectations Grow, Data Analytics Faces Hurdles
Expectations from data analytics in the upstream sector continue to evolve. Although the number and diversity of applications continue to increase, the adoption at the assetwide level faces well-known barriers and challenges.
Simulation Algorithm Benefits by Connecting Geostatistics With Unsupervised Learning
A new geostatistics modeling methodology that connects geostatistics and machine-learning methodologies, uses nonlinear topological mapping to reduce the original high-dimensional data space, and uses unsupervised-learning algorithms to bypass problems with supervised-learning algorithms.
Face-Detection Algorithm Handles Big Data To Help Identify Candidates for Restimulation
This paper demonstrates the viability of a production-data-classification approach adapted from real-time face detection for identifying restimulation candidates.
New Method for Predicting Production Boosts Accuracy for Carbonate Reservoirs
This paper proposes a new method of economic prediction on the basis of expert library and oilfield databases. The method takes into account geological factors and the effect of production factors on the economic prediction.
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14 October 2019
07 October 2019