Capricorn

Leverage the benefits of having all prospects in a secure, central database

PLDB – Prospects & Leads

Capricorn Energy has, for many years, been mastering all prospect information in spreadsheets. As they continued to explore, observing how their portfolio of prospects increased and regional focus and balance of priorities evolved, they needed to assess what technology was available to help improve efficiency in the assembly and analysis of prospects, so that investment portfolios can easily be prepared and reviewed on demand.

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Regional mapping of key horizons

Petrosys PRO
CONSULTING

A regional exploration team at a large NOC needed to map key reservoir horizons across four producing oil fields, that while geographically adjacent to each other, were for a long period developed separately, where there was no exchange of knowledge between the separate Asset Teams.

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Quickly convert legacy data to digital formats

Petrosys PRO
CONSULTING

A new entrant to a mature basin needed to gather surface and fault data from many images and scanned maps. Traditional digitising was slow, boring, and unpopular with the team, useful knowledge was being excluded because it was too difficult to capture.

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Improve geological accuracy of subsurface maps

Petrosys PRO
CONSULTING

A new venture exploration team needed to map prospects in a highly faulted area. They knew the faults were present in their area of interest, but some were not being picked up by auto-tracking software – it became clear that to get what they wanted they would have to improve the geological accuracy of the subsurface maps.

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The Objective: Identify Target Exploration Companies

GPinfo

PGS Australia were looking to conduct targeted marketing for offshore Western Australia. They wanted to identify exploration companies with a seismic commitment in the upcoming year and knew GPinfo could be used to produce the actionable information.

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Improve spatial sampling of legacy datasets

GLOBEClaritas

There is a significant amount of vintage seismic data available, which if sensitively reprocessed could provide a lot of value. However, poor spatial sampling and therefore spatial aliasing of these vintage or legacy datasets remains a significant problem.

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