Author: Azucena Gomez
Global Business Manager
Author: Satyam Priyadarshy, PhD
Halliburton Technology Fellow for Data Science
Most major oil companies today have embarked on digitalization programs in response to the impact of cumulative downturns in the industry that occurred in 2014 and 2020. But while the rest of the industrial world is venturing toward digital transformation, the oil and gas sector is still slow in adopting the next phase of digital journey beyond digitalization. The foundational pillars of digital transformation are: Big Data Analytics, the emerging computing paradigm, real-time insights and actions, and autonomous systems.
Big data analytics relies on data science to explore and expose inefficiencies in the oil and gas industry’s workflows, processes, and operations. However, to maximize the value a well-thought out approach to leverage data science is essential. There are several publications that talk about failure to derive value from data science, Big Data and digital transformation. These failures are primarily due to incomplete and inconsistent approach to addressing the use of data science in our industry. Over the last 6+ years, Halliburton Landmark has successfully developed its data science approach and has been able to demonstrate multi-million-dollar economic impacts across the oil-well life cycle.
Our mission is to collaborate and engineer solutions to maximize the value of assets, and our data science approach, where data is the asset, is true to this mission as well. Halliburton has 100+ years of experience in the upstream oil and gas industry. By incorporating this industry experience with that of our customers we can help you to maximize the value of your data assets. The Landmark business line has developed solutions to manage data and information across the oil-well lifecycle. Our experience with all possible petro-technical data (e.g., seismic, log, production, reservoir, real-time, etc.) and our expertise that lies in the industry’s first Big Data and Data Science Center of Excellence has generated significant value from 20+ data science engagements globally. Our approach is to generate value in a phased manner, thus reducing any capital or operational costs associated with data-driven innovation since most oil companies have multiple challenges with their data.
Our focus is to generate a proven economic value in each of the phases as measured by one or more of the economic value metrics such as accuracy, NPV, cost savings, efficiency, etc. Here are some of the examples of the proven economic value through data-driven innovation:
True to our mission to maximize the value for our customers/partners, we pioneered the concept of talent transformation for petrochemical professionals to learn and leverage big data and data science skills in their daily jobs. We developed highly contextualized and customized masterclasses for our industry professionals so the time to create value from lessons learned is minimal. We have transformed 500+ professionals in multiple companies through these masterclasses. We also pioneered and deliver Executive Digital Seminars and Summits for our customers’ top leadership and managers. The focus of these executive sessions is to reduce the digital divide that exists in companies. To help our customers build business cases for data-driven innovation, we developed and deployed SmartDigital™ workshops, so all members of teams can speak the same language for digital transformation, data science, and areas to focus on to generate value.
We deliver value in a phased manner, as it provides a smoother roadmap to operationalize, and industrialize data science at scale in the organization, thus minimizing the impact of distracting events or activities. For example, we deployed models on a Latin America region NOC, successfully coupling their current data systems and third-party vendors.
Our contextualized and customized approach of building, testing, scaling, deploying, and maintaining AI/ML models has proven successful, and has helped reduce capital expenditure, and lost time due to inefficient and ineffective use of data.
To learn how Halliburton Landmark’s mature, scalable data science models and our SmartDigital™ co-innovation service can work for your organization, request a demo.