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Program

Industry 4.0 revolution has changed the traditional business landscape. Automation, connectivity, and intelligence are driving the digital transformation of various industries. The convergence of information technology and operations has led to the emergence of cyber physical systems, which have permeated every aspect of our lives.
Digital technologies combined with data-driven insights are transforming operations, improving productivity, boosting effectiveness, and improving decision-making along the entire E&P value chain.
Let the E&P experts share their experiences during the conceptualization, development and deployment of digital products and data-driven solutions that have created real-world impact in the upstream oil and gas industry.

> See the schedule from Energy in Data 2021

Digital Journey–Lessons captured to invoke the next frontier of innovation

Organizer–Sid Misra

TAMU Collaboration Team:
Eliza Ganguly, Keyla Gonzalez, Rui Liu, Cody McIntyre, and Julian Uribe

Schedule

Download schedule at a glance pdf

Monday, 12 April 2021

Click on a session to learn more.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University

This presentation will cover the need for change with the global energy future, requirement for carbon management, cross disciplinary integration, and how digitization can act as an integrator. The content will be delivered through a specific case study from Colorado School of Mines to show how this is being addressed in higher ed.

Speaker
John Bradford
Vice President of Global Initiatives and Dean of Earth Resource Sciences and Environmental Programs
Colorado School of Mines

Conventional oilfield market intelligence relies on downloading, processing and mapping various state regulatory filings, such as drilling permit submissions and production and completion reports. Regulatory sources have a number of shortcomings: they are often slow to report, incomplete and inaccurate.

New technologies for gleaning oilfield activity from independent, nonregulatory sources may enhance the timeliness, accuracy and completeness of market intelligence used for energy business decisions. One such independent source is satellite imagery. High cadence, high resolution satellite imagery has become commercially available in recent years, as have the software tools and processing power needed to analyze vast areas reliably on a daily basis.

Sourcewater, Inc., an energy intelligence company launched from MIT, has developed machine learning and artificial intelligence technologies to detect and analyze energy activity in satellite imagery that is missing or delayed in regulatory data, such as frac ponds, well pads and frac crews. The company has been granted nine U.S. patents for its innovative machine learning and image processing methods in the energy sector. This session will cover some of those methods and the results of a recent study in which the time and probability relationships between satellite-imagery well pads, drilling permits and drilling events were analyzed for over 12,000 Permian Basin wells.

Speakers
Joshua Adler
Founder & CEO
Sourcewater

Hydraulic fracturing stimulation designs are moving toward tighter spaced clusters, longer stage length, and more proppant volumes. However, effective evaluation of the hydraulic fracturing stimulation efficiency remains a challenge. Distributed fiber optic sensing, which includes Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS), becomes a promising tool that highlights the processes relevant to the completion. Distributed fiber optic sensing usually generates a large volume of data, tens to hundreds of terabytes. How to process such large volume of data rapidly and allow geoscientists and engineers to interpret the measurements to fluid allocation intuitively becomes a key for completions decision making. To make such decisions happen in field requires edge and high-performance computing infrastructure at the well site. In this session, we will show a proposed end-to-end application developed from the raw data processing to fluid allocation during hydraulic stimulation. It will include the workflow developed to rapidly process and interpret fiber optic data, the edge computing system solution employed for rapid data processing, and the solution architecture of the application. We will give a demo using an example of a hydraulic fracturing monitoring for a Wolfcamp well in the Midland basin.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Vikram Jayaram
Pioneer Natural Resources
Shuang Zhang
Pioneer Natural Resources

Standard production forecast techniques for unconventional asset development rely mostly on field data, which could suffer from limitation in both data quality and quantity. It is also a challenge to interpret subsurface dynamics directly from field observations. In this immersive session, we explore a workflow that can enable decision making for unconventional development through organic combination of field and simulation data. It provides physics based well performance forecasting, interpretation, and uncertainty estimation—all without running additional reservoir simulation during inference.

This session will include discussion about use of physics based simulation models, exploratory data analysis, as well as aspects of training and interpretation for machine learning models.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Kainan Wang
Chevron
Elena Rodriguez
Chevron

3D numerical methods for predicting hydraulic fracture geometry and subsequent production forecast have been adopted by many shale operators for planning and evaluation purposes. However, operationalizing the numerical simulation-based workflow for completion design optimization remains a challenge owing to its slow model-to-design turnaround cycle. In this session, we will apply machine learning models to create proxy of the entire dynamic process of a state of art stimulate-to-produce workflow, for completion design and related high-level decision making. The novel aspect of the approach is that the "big data" scenario is essentially generated from simulated data instead of raw data. One caveat of this methodology is that it still requires building a physics-based model. We will discuss the development of a generic solution using an array of inputs to go beyond the limitation.

The demo session will include construction of physics based model and software workflow; cloud computing capability for hydraulic fracture design and production simulation; exploratory data analysis on simulation data results; and train and test model with multiple regression models with Python’s open source library as well as our recommended API.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Raj Malpani
NAM Technical Manager - Reservoir Stimulation
Schlumberger
Hannah Xue
Sr. Reservoir and Production Stimulation Engineer —Software Integrated Solutions (SIS)
Schlumberger

Fluid Properties and Relative Permeability data are used in multi-disciplinary applications, from reservoir evaluation to reservoir performance management. In this session we will focus on various aspects of prediction of such data and how to utilize the physics based content knowledge along with data-centric approaches:

  • Current landscape and the workflows
  • Deficiencies in both physical and as well as in correlative models
    • Seeking for quantitative proxies and their existence
  • Physics augmented/hybrid approaches by examples
  • Discussion
Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speaker
Birol Dindoruk
University of Houston and Shell
Silviu Livescu
Baker Hughes

Tuesday, 13 April 2021

There are volumes of data collected by oil and gas operators, service companies, and governments. Leveraging the data to explore opportunities that lower the cost of finding and extracting oil and gas is critical in today’s market. However, Digital Transformation, Data Science, and AI are just the beginning of the journey to lowest cost BOE. Organizations that can leverage data across borders and company lines to create better outcomes while meeting government regulations and company guidelines is the next major step in the O&G digital journey.

Speakers
Marc Spieler
General Manager
NVIDIA Energy Industry
Ken Hester
Global Solution Architect Manager - NVIDIA
NVIDIA Energy Industry

The Oil and Gas industry is facing a tremendous amount of change, especially over the past year. Global demand that plummeted due to the pandemic is expected to recover, but not to pre COVID-19 levels, putting pressure on O&G companies to cut costs and modernize in order to stay relevant and outperform their competition, but where should an organization focus it's efforts? Often, lack of access to critical information is a factor, companies managing Onshore and Offshore operations without real-time insight to their resources suffer from inefficiency that increases safety risks, lowers productivity and drives up expenses. In response, forward thinking O&G companies are turning to mobile and edge computing technologies to close information gaps, increase efficiency and reduce costs.By providing a fast and reliable flow of critical information, modern mobile, IoT and edge technologies enable better decisions in the field by offering data processing and real-time analysis, even when internet connectivity is not available, such as offshore or in remote, rugged locales. This session discusses the emerging technology advances in mobile and edge computing and explores how these solutions can improve an Oil and Gas companies efficiency and reduce costs in areas such as drill rig maintenance, pipeline monitoring, well maintenance, inspections, workforce management and more.

Speakers
Mark Gamble
Product & Solutions Marketing Director
Couchbase

Both Baker Hughes and P&O Maritime Logistics will connect participants live to a marine vessel, currently located in the ocean off the coast of Dubai. VitalyX will show live data feeds from both the engines on board. Just as new technology in the health care industry can show live health results, VitalyX is the equivalent for industrial machines. Participants will learn to analyze the live data feed and about the operation of those engines using real-time monitoring of the lubricants. Baker Hughes and P&O Maritime Logistics will then invite participants to suggest ways in which this solution can be improved, and what other inputs could be used to protect an assets health.

Learn about how digitization is changing in the marine industry and discover how operators are working with certification bodies on digitizing the industry. Understand how new partnerships are changing the traditional model of a buy/sell relationship and how this is key to implementing digital technology.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Glen Parkes
Digital Product Management Director
Baker Hughes
Kris Vedat
Chief Information Officer
P&O Maritime & Logistics

The integrated digital twin will help oil and gas operators in two different stages. In the field development stage, the design of the subsea field will be done in the cloud-based platform (engineering simulation, optimization and automation will be performed in a cost-effective way using a single source of data concept). In the operation stage, the same digital twin will access the operational data through sensors, etc. (and compared with the simulation results from design stages to develop predictive maintenance strategy and help the operators to reduce the maintenance cost). There will be a live demo of our cloud-based platform for subsea field development and some field development automation.

Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Subrata Bhowmik
McDermott
Gautier Noiray
McDermott
Harsh Patel
McDermott

Real-time analysis, monitoring and decision-making bring huge advantages to the drilling and completion operations by improving the operational efficiency and safety, as well as reducing cost. Currently the common implementation in the industry is “near” real-time control center or “near” real-time cloud computing. We will show the participants a TRUE real-time analytics-driven decision-making system that is developed by deploying the stream processing engine and powerful edge computing hardware at the well site, which also enables potential close-loop control optimization. The highlights of WPX’s edge computing solution are:

  1. Highly cost effective. The system is based on open source Apache Kafka ecosystem, backed by the commercial vendors.
  2. Designed for Edge Computing. Edge computer and Apache Kafka has been deployed to edge for stream processing.
  3. Drilling and completion service provider agnostic (data source agnostic).
  4. Cloud provider agnostic.
  5. Scalable with rig/crew count at negligible cost.
  6. Low maintenance, non-technologist installation/deployment edge computers.
Moderator
Sid Misra
Associate Professor in Harold Vance Department of Petroleum Engineering
Texas A&M University
Speakers
Dingzhou Cao
Senior Data Science Advisor
WPX Energy

More information will be coming

* NOTE: All times are CT

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