Introducing an Integrated Prospect Derisking Tool

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The September issue of First Break highlights an innovative workflow for real-time modeling of reservoir quality in areas with complex geology and/or limited well control. The approach integrates burial history with basin and rock physics modeling and is constrained by full waveform inversion velocities. This work is a collaboration between PGS and Dig Science.

Read the full paper ‘Exploration workflow for real-time modeling of rock property and AVO feasibilities in areas with complex burial history — a Barents Sea demonstration’

A major challenge for the industry is to fast-track oil and gas exploration and production from subtle and complex traps more efficiently than before. Integration and automation are key aspects in this process and the paper demonstrates how a novel, integrated and seamless workflow enables geologically constrained and robust real-time prediction of expected rock physics properties away from well control.

Prospect derisking away from well data
In areas with few wells and complex geology, it is challenging to predict reservoir quality in surrounding prospects away from well control. The new workflow uses FWI velocities as input to constrain burial history in areas without well control.


A Workflow For All Geoscientists

3D cubes can be generated for any given geological scenario and assessments made on the sensitivity of the elastic response to the input parameters. These can be used to guide, validate, and calibrate quantitative interpretation studies and to derisk prospects.

An example from the Barents Sea illustrates how the proposed workflow can efficiently derisk DHI leads and prospects in a complex geological context. More specifically, it allows the interpreter to account for and analyze the impact of geological information like sand and clay types or tectonic uplift on the final geophysical interpretation, and to run sensitivity analysis of key input parameters in real-time.

Such a workflow can support complex prospect risking procedures and the estimation of risked volumes of hydrocarbon. This can provide an integrated organization-wide consistent approach to the DHI-modified risking process used by the industry.

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