Data Examiner

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  • Article Written By AUTHOR - Nhung Nguyen, FACULTY MENTOR - Konstantinos Kostarelos, Department of Petroleum Engineering, University of Houston

    Abstract: The goal of this work is providing details analysis on two unwanted gas treating methods to encourage a zero gas venting/flaring future in the Permian basin. The main concepts of each method will be discussed along with details of a suggested method and its challenges.

    The first step is conducting a brief study about the Permian basin. Reports on greenhouse gas emission in the area are showed to reflect the bad effects of unwanted gas venting/flaring practice. There are two main methods discussed: associated gas reinjection and underground gas storage... Read more > 


  • Article Written By Vuong Van Pham1, Ebrahim Fathi2,*, Fatemeh Belyadi3

    1 University of Kansas; vuongvanpham@ku.edu
    2 West Virginia University, USA
    3 Integrated Smart Data Solutions LLC, Fatemeh.belyadi@gmail.com
    * Correspondence: ebfathi@mail.wvu.edu

    Abstract: A new hybrid approach for developing Machine Learning (ML) workflows is proposed to automate algorithm selection and hyperparameter optimization. The proposed approach provides robust and unbiased workflow that can be validated using different scoring metrics. The most common workflows implemented in application of Artificial Intelligence (AI) and ML in engineering problems are compared with the new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation and Mean Square Error... Read more > 


  • Article Written By Lori Bryan, Texas A&M University

    The modern economy is driven by information, and data is now thought of as a commodity. Unlike physical assets such as petroleum products, minerals, or equipment, data assets are neither finite nor consumable (Henderson et al., 2017). Data assets are only valuable when they are used, consumed, and/or applied to business intelligence. The term "big data" refers to data that is so large in volume, variety, veracity, velocity, and value that it is too complex to manage with traditional relational databases (Mohammadpoor & Torabi, 2018). Upstream Oil and Gas data falls into the category of "big data" and must be managed as such.... Read more > 


  • Article Written By Victoria Artell, Smart Data Solutions, CGG

    With the objectives of OSDU being to reduce data silos, provide workflows in the cloud, and improve access to all metadata, there remains the need to condition, manage and load data into systems while conforming to or aligning with data and IT standards (such as TOGAF®, DPBoK™, Agile, etc.) to enable integration into wider agnostic systems and portals, both from a data and technology standpoint. Yet the OSDU does not solve all of these challenges. Many of the same data management challenges persist... Read more > 


  • Article Written By the PPDM Associations Certification Committee

    1. Understand the need for Data Governance Organizations of unstructured and structured data for workflows (document management, attribute standards, naming conventions, metadata capture, raw vs. interpreted, audit trails, and best practices)
    2. Broad and complex scope of E&P Knowledge used for Communication and Master Data Management Liaison in communications and interactions with other departments for data assets from seismic, well, ... Read more >

  • Article Written By Yogi Schulz, Corvelle Consulting

    We’ve all read articles extolling the limitless potential of artificial intelligence (AI) and its cousin, machine learning (ML). As an E&P data analyst, you may be nervous about the sluggish progress your AI/ML project team is making after having slid by multiple milestones. You are worried that management will lose patience and cancel what you see as... Read more > 


  • Article Written By Amii Rozell, Director, IHS Markit

    Gone are the days when data organization used to be as minimal as simple rows and columns. All sorts of data types emerged since the internet invaded our lives and changed the technology industry, including the data management world. Proper data management today is more than just tables and rows grouped in a string format; more than just structured, or even semi-structured data stored in a relational database. Oil and gas companies need a dynamic way to store, manage, and maintain quality data for decision-making. Why? Well, today, oil wells are not the most important asset in the oil and gas industry; data is. Companies deal with a huge amount of data from different phases of the well's lifecycle such as exploration, drilling, and production and that data is increasing dramatically every day. The energy industry's problem today is that oil and gas companies cannot capture all the data they need to make better decisions faster.

    Organizations need the ability to store and manage ALL data including unstructured. From that internet disruption, NoSQL (“Not only SQL”) appeared, and the threat to SQL’s existence... Read more >


  • Article Written By Jim Crompton, Reflections Data Consulting LLC

    The world’s 7.5 billion people need a vaccine for COVID-19 as soon as possible. Earlier this year it seemed that one or two pharmaceutical firms might be able to obtain some sort of approval by the end of the year. But now many large drug companies are pledging to uphold scientific and ethical standards in the search for an effective vaccine. Many experts are now telling us that it may be mid-2021 before the majority of us will have access to a safe vaccine.

    There is a big trust issue behind all of this. Most modern countries have well established processes to ensure safety of products before they are released... Read more > 


  • Article Written By  Trudy Curtis, CEO, PPDM Association

    For thirty years, the mandate of the PPDM Association™ has been the development of the data management professionals, along with the standards and best practices that ensure petroleum data continues to evolve as a trusted and relevant asset both for its members and industry as a whole.

     

    The Open Group Open Subsurface Data Universe™ (OSDU) data platform will revolutionize industry’s ability to deliver new subsurface capabilities through the creation of an open, standards-based ecosystem that drives innovation and accelerates the deployment of emerging digital solutions for better decision making. Industry participation in The Open Group OSDU™ Forum and support...Read more >


  • Article Written By Jim Crompton, Reflections Data Consulting LLC

    For all of you who are Game of Thrones fans like I am, the phrase “Winter is Coming” is a very familiar one. For those of you who are not, here is a brief description from gameofthrones.fandom.com: "Winter Is Coming is the motto of House Stark, one of the Great Houses of Westeros. The meaning behind these words is one of warning and constant vigilance. The Starks, being the lords of the North, strive to always be prepared for the coming of winter, which hits their lands the hardest.”

     

    Now this is not another blog about the Game of Thrones story. Nor is it a warning on a coming ice age or invasion of the Night King and his zombie army. It is actually an article on artificial intelligence. In a recent Economist Technology Quarterly story (June 13th, 2020), the limits of the progress of artificial intelligence is discussed. For those of you who know me or have followed my articles, you will know that I love to take the counter argument for any tech trends that gets overhyped, so this time to topic is AI.... Read more >