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.

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.

STEPS Theme 2 Big Data in Exploration & Production Student Presentations


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