Digital Energy Journal- OPINION: What IT would best help geophysicists?

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OPINION: What IT would best help geophysicists?

Friday, April 1, 2016

What does competitive advantage IT look like from the perspective of a geophysicist, geologist or seismic interpreter?
Thoughts from David Bamford, a former head of exploration with BP (and columnist for Digital Energy Journal):

Ultimately, subsurface science can be summarised as 'drilling profitable wells'.

The key is to learn how to do this in a predictable, repeatable way (as opposed to drilling 'on trend', in a pattern, or effectively randomly).

We are really detectives, subsurface detectives, taking scraps of evidence, all sorts of expert insights, and coming up with a story.

The available methodologies are rule-driven interpretation; data mining (using analytics); modelling and inversion.

Rule-driven interpretation

Well-established 'rules' have been proven for stratigraphy, structural geology, sedimentology and describing petroleum systems (especially by creating Gross Depositional Environment (GDE), common risk segment (CRS) and composite common risk segment (CCRS) maps. Nowadays these 'rules' are most commonly applied through seismic data, especially 3D seismic data.

The key 'technologies' are a) large quantities of inexpensive multi-client 3D seismic and b) commoditised interpretation workstations.

In truth, this methodology has now become completely commoditised. Little commercial advantage accrues from getting it right, simply disadvantage flows from incompetent execution.

Thus, if future competitive advantage is to be found, it must lie in either data mining - applying analytics to data sets that are so large that they do not allow easy interpretation by humans - or modelling and inversion - especially those using and/or integrating more powerful geophysical technologies than towed streamer 3D seismic!

Data mining

We can access satellite and airborne data, a significant variety of well results (logs, cuttings, core, flow rates), potential field, seismic, surface geology from a wide range of proprietary and public sources in diverse formats, with different accuracy, coordinate systems, and units of measurement.

We can be confronted with truly huge amounts of data and it is critical that we extract the key information from all of it rather than looking at only a sub-set and/or simply entering the analysis with a 'going-in model' which we then look to authenticate.

Analytic techniques allow us to do this.

The key 'technologies' are a) the ability to integrate large quantities of diverse data, and b) fast 'analytics' applications, tuned to the problem in hand.

Modelling and inversion

Predicting physical properties such as density, magnetic susceptibility, electrical conductivity, seismic velocity from geophysical data whether gravity, magnetic, electro-magnetic or seismic. Also addressing complex subsurface structures.

Of all these technologies, seismic remains the most powerful, offering the least ambiguity and the most resolution, providing a framework into which other geophysical data can be integrated.

The key 'technologies' are a) integration of physically diverse multi-measurements, and, b) currently 'niche' inversion + modelling applications.

The team

And so, we can make a conclusion about who does this work, in a team of subsurface detectives.

Rule-driven interpretation requires seismic interpreters and geologists
Data mining requires data scientists.
Modelling and inversion requires geophysicists

Integration being the key to beating the competition!

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