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Abstract

Petroleum geoscientists and engineers will rely heavily on automation and statistical analytics in the near future in most disciplines, particularly for geomodeling. The recent downturn in the industry and the sluggish return to more favorable oil prices, coupled with the impending “big crew change,” will spawn fewer domain experts to produce viable drilling projects, particularly in unconventionals. Industry will look to universities to broaden their petroleum curricula in order to cultivate students with wider disciplinary expertise – expertise that enriches their principal domain. Graduates will not only need to blur the divisions between geoscience and engineering, but they will also need to have substantial expertise in areas like data science and computer engineering. This means that geoscientists and engineers will further develop left-brain and right-brain activities, respectively.

The implications to geomodeling, the building of static models, are significant. In fact, we can foresee the merging of static and dynamic models to produce a single geo-reservoir model. Current barriers to produce such a model like grid size, identification of key variables, flow equations, and time-steps, will be broken down in the presence of cloud computing, seamless workflows, machine learning, and advanced particle physics that overcome barriers between solid and fluid mechanics, which are already working their way into our space from other disciplines.

While this rather diverse set of skills may reduce deep expertise in any one individual sub-discipline, the iconic domain experts of today will very likely be smart, cloud-based machines. These computers will talk to each other and enrich themselves through constant, real-time assessments of massive data stores, and deliver exploration and production nuggets of cognitive learnings to new-age petroleum scientists. In the near future, geoscientists and engineers will behave much more like pilots than carpenters.





Speaker | Dr. Jeffrey Yarus, Halliburton Technology Fellow for Landmark

Dr. Jeffrey Yarus is a Halliburton Technology Fellow for Landmark with over 41 years of industry experience. His specific areas of thought leadership include earth modeling and geostatistics, and he is the principal lead for the DecisionSpace® Earth Modeling module. Early in his career, Dr. Yarus enjoyed the opportunity to work with a number of major oil companies and technology service companies, including Amoco, Marathon, Beicip-Franlab, and Roxar. In 2001, he helped found a consulting company, Quantitative Geosciences (QGSI), specializing in applied earth modeling. The QGSI staff, along with Dr. Yarus, joined Landmark Graphics Corporation in 2006 to build an earth modeling software product; today a core module on the DecisionSpace® Geosciences solution suite.

Dr. Yarus earned his PhD and master’s degree in geology from the University of South Carolina and his bachelor’s degree in geology from the College of Wooster. He served as chair of a number of AAPG’s committees including the Computer Applications, Publications and Reservoir Development committees. He has authored many papers and abstracts on reservoir modeling and geostatistics, including AAPG volumes on stochastic modeling and geostatistics, the chapter on reservoir characterization and geostatistics and the SPE Petroleum Engineering Handbook, Volume VI. An acknowledged lecturer and author in the industry, Dr. Yarus earned the distinction of 14-year Adjunct Faculty Member for the University of Houston’s Department of Petroleum Engineering and Contributing Editor of the Stochastic Modeling volumes in AAPG’s Computer Applications Series.

THREE REASONS TO ATTEND:

  • Tune in to what the future industry reality will be for geologists and engineers
  • Hear how geomodeling will evolve as technology breaks down barriers, allowing the emergence of static and dynamic models
  • Get insight into how today’s domain experts will be giving way to experts that are smart, cloud-based machines

TARGET AUDIENCE:

  • Geoscientists
  • Geologists
  • Geophysicists
  • Geomodelers
  • Engineers
  • Asset Managers
  • Engineering Managers
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