LIVE WEBINAR – Hydrocarbon Prospectivity Successfully Predicted Using Only a Teaspoon of Soil

Kindly supported by Rock Flow dynamics

This live webinar will take place at:

11am              – Perth
12.30pm       – Darwin
1pm                – Brisbane
1:30pm          – Adelaide
2pm                – Canberra, Hobart, Melbourne, Sydney

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Hydrocarbon Prospectivity Successfully Predicted Using Only a Teaspoon of Soil

Presented by Jonathan Zwaan from Biodentify

Abstract

Dutch tech company Biodentify has developed a technique to predict hydrocarbon prospectivity through DNA analysis of shallow soil samples. With this technique drilling of wells and prospects can be de-risked. In this presentation Jonathan Zwaan will explain the technique and show the results of two projects: one in a conventional setting in central Argentina, one in an unconventional setting in the Bakken (North Dakota) and the Eagle Ford Shale (Texas).

Argentina Case Study

In 2018 Biodentify was awarded a research grant by EU Horizon 2020 fund. The Argentina Project was the first of several research pilots. Together with an operator we chose an area where samples were taken over a shallow oil field, a deeper gas field and a non-hydrocarbon, or dry area. For 800 samples the hydrocarbon data remained known to us, 300 samples were re-labelled and blinded by the operator in order to be able to validate our predictions.

USA Case Study

The USA project was performed together with two operators, where two areas were chosen with known well production statistics. In these areas a total of 540 samples were obtained above the 5% highest and 5% lowest producing wells. From the 540 samples, 200 were re-labelled and blinded by our customers, to be able to validate our predictions. 

DNA Sequencing and Machine Learning

For each project the soil samples, half a teaspoon in volume and taken at a depth of 1 foot below the surface, were sent to our lab where DNA sequencing was performed. Lab results show which microbes are present in each sample and their relative abundance. Through advanced machine learning algorithms and our own metagenomic pipeline we are able to accurately predict for the Argentina case whether the sample is taken above one of the oil/gas fields, or above a dry area. And for the USA case: whether the sample is taken above one of the best or one of the worst producing wells.

Methodology Background

Biodentify’s technology is based on the response elicited in the microbial population in the shallow soil (<30cm) by trace hydrocarbons which have migrated from depth to the surface through vertical microseepage. These trace hydrocarbons released are otherwise undetectable, but the bacterial population acts as an extremely sensitive indicator. This very small signal can be picked up using Next Generation Sequencing and recent advances in Machine Learning.