Using machine learning to identify remaining hydrocarbon potential
Are you an expert in big data? Do you have a machine learning solution? Then get involved with our Digital Transformation 'Call for Ideas'. The 26 Jan deadline is fast approaching.
We're investing c.£1 million in a portfolio of projects to solve our Digital Transformation challenge but all we need at this stage is the spark of an idea.
What's the Call for Ideas all about?
Many oil and gas fields in the Northern North Sea (NNS) are nearing the end of their expected operating lives. If new sources of hydrocarbons are not found, then much of the production infrastructure (e.g. wells, pipelines, risers) may be decommissioned in the near future.
There are large volumes of data from NNS oil and gas wells that could lead to new discoveries, but it is often held in different formats and of variable quality and takes time to assess.
Traditionally, organising, distilling, screening and assessing data would require a large team of specialists, and there is always a risk of a person missing something or introducing bias into the evaluation.
We’re looking for digital analytics approaches, such as machine learning, that can deliver assessments of structured and unstructured well data quickly and accurately.
The aim is to use the available data to identify and classify intervals which may indicate the presence of previously unrecognized or overlooked petroleum accumulations.
This would allow the industry to fully evaluate these opportunities and prioritise investment, potentially extending field life and maximising economic recovery.
We would like to hear your ideas to help with this challenge.
Nick Richardson, Exploration and New Ventures Manager at the Oil and Gas Authority:
“The MER UK Exploration taskforce is delighted to sponsor the Call for Ideas and is eager to see how the latest analytics techniques can transform the huge volumes of well information and illuminate the remaining exploration potential in the Northern North Sea.”
Malcolm Fleming, CDA's chief executive, said:
"As the provider of shared services for managing UK continental shelf (UKCS) subsurface information, CDA supports moves to implement advanced technology, including machine learning. This will help to extract even greater value from the wealth of well and seismic data available in our UKOilandGasData system, whether to improve exploration success, or to maximise economic recovery from late life fields."
If you have any questions, please email email@example.com.