STEPS Theme 2 - Big Data Science in Exploration and Production

Big data is a growing challenge throughout all industries, and Exploration and Production is no exception. Disparate, diverse and ever-growing geologic datasets are readily accessible across multiple platforms and now, more than ever, need to be utilised in ever-shortening time frames.

This year’s research theme will focus on how we can overcome the ‘Four V’s’ — volume, velocity, variety and veracity — of Big Data, to make efficient and comprehensive interpretations of the subsurface.

The 2017/2018 'Big Data' projects cover a diverse range of issues and each require a multidisciplinary approach to the solution — be that a geologic interpretation of the development of a new workflow.  Student geoscientists and data scientists interested in the E&P industry will benefit form these projects by;

  • Experiencing real-world data
  • Utilizing large and disparate datasets
  • Defining a methodology to resolve an issue or make an interpretation
  • Working within the cloud environment
  • Gaining experience with industry standard computer applications
  • Receiving guidance and support from industry professionals

STEPS Theme 2 project listing 2017/2018

Project Number
Project Title
BDEP_01
Linking hinterland hard-rock geochemistry to sedimentary reservoir compositions: implications for sediment quality predictions in frontier areas. 
BDEP_02
North Sea plays providing analogues for frontier rift basins.
BDEP_03
Towards a globally consistent maturity assessment: a statistical analysis of maturity parameter conversions to vitrinite reflectance equivalence.
BDEP_04
Predicting gas souring risks to petroleum systems.
BDEP_05
Filling missing well data for improved geomodelling.
BDEP_06
Global paleo-landscape modelling through deep-time applying large geochronology and thermochronology datasets.
BDEP_07
Generating Chronostratigraphic Sematic Ontologies for step-change E&P analysis.
BDEP_08
Predicting uplift in the Appalachian Basin by numerical modelling of multiple temperature sensitive datasets and its impact on unconventional hydrocarbon exploration.
BDEP_09
Modelling themochronology data for predicting the landscape evolution and offshore sediment flux patterns of North America.
BDEP_10
Evaluating reservoir potential on the North Atlantic margin – insights gained from integrating multiple datasets.
BDEP_12
Automated history matching for a reservoir simulation model.
BDEP_13
Analysis of subsidence trends to understand the factors influencing accommodation space generation of passive margins.
BDEP_14
Assessing the maturity of the Monterey Formation, offshore California
BDEP_15
Porosity and permeability trends for clastic reservoirs across Afro-Arabia.
BDEP_16
Machine learning in paleoenvironmental determination from Biostratigraphic Data.
BDEP_17
Data Science applied to Plate Tectonics.


The tender window for STEPS 2018 projects is now closed. All applications will be reviewed by our Scientific Advisory Board and successful applicants will be notified by email. If you would like to discuss your application, please email STEPS@Halliburton.com.

The associated 'Big Data in Exploration & Production' Distinguished Lecture Series has now concluded.  To view the recordings of past lectures, please visit the Distinguished Lecture Series page.

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