BIODENTIFY is a venture of TNO and JOA since 2015. Biodentify is headquartered in the University City Delft, The Netherlands. TNO is a 4000+ Dutch R&D organization, hosting the largest Microbiological research group in the Netherlands. JOA is an internationally Oil and Gas technology supplier providing e.g. modelling & software tools and light weight proppants manufacturing.

The result of this cooperation is a novel technology, predicting sweet spots in shale oil and gas plays before drilling with approx. 70% accuracy, based on microbiological DNA analysis of shallow soil samples.


Real Game Changer by producing ‘High Accuracy Sweet Spot Maps before drilling’

The Patent Pending sweet spotting technology targets reducing the amount of wells by stepping away from grid drilling and implement an iterative procedure of prioritized development of higher profitable areas of a play. Besides cost reduction by not drilling low producing wells, it is also a way forward in higher development speed and more effectively use of available/affordable drilling rigs. This is accomplished by producing a >70% accurate predictive map with the presence of sweet spots, using DNA anlysis of shallow soil samples, prior to drilling.

Highly effective exploration drilling and investment/desinvestment decision making.

Significant cost reduction by optimized drilling scenarios (no grid drilling) and by increased development speed of a play. The accuracy of the predictive map is iteratively increased with approx. an extra 10% by incorporating information of the drilled wells with field type specific information.

Cost reduction by optimizing fracking scenarios.

Technology & Process

A technology – has been developed to analyze surface soil samples (few mm3’s from approx. 1 ft. depth) that recognizes hydrocarbon micro-seepage from sweet spots. First, bacterial DNA is extracted, producing tagged 16S rDNA data that is translated to bacterial species. The result of this ‘DNA technology’ is hundreds of thousands (partly field type specific) biomarkers. The ‘DNA finger-print’ of the soil sample.

Our database – with biomarkers, is subsequently used as modeling input to our proprietary localized triple loop © computational model, capable of predicting the presence of a sweet spot in a heterogeneous field with an accuracy of 70-80% prior to drilling. It basically uses the difference in ‘DNA finger-prints’ connected to sweet spots and non-sweet spots. As the extend of field specific information increases, e.g. by drilling and producing of wells, the accuracy of the sweet spot prediction can increase even further.

The presence of vertical upward microseepage is extensively described in the literature where clear and sharp anomalies of microbial population and geochemical properties could be found precisely at the border of reservoirs. Bacteria are present in high numbers and variation of species in soil samples. Their exceptionally high adaptivity to grow on small amounts of nutrient sources from the shale ‘reservoir’ turns them into an advanced ‘soft sensing mechanism’.

The Patent pending workflow – consists of the following steps:

  1. Sample soil on a grid. (grid spacing optimized for sweet spots size)
  2. Build model with proprietary ‘DNA finger-print’ data.
  3. Predict on grid and generate a first Sweet spot prediction.
  4. Drill in predicted sweet spot(s).
  5. Increase prediction accuracy by iterative re-modeling using the information from drilled wells.

In parallel with TNO’s medical DNA validation practices, the sweet spot prediction accuracy given above has been extensively validated. For the in the mentioned plays, the initial prediction accuracy is 71-84%, thousands of sampled locations with analyzed DNA / biomarkers and known production history have been run as validation set.
For one simulation, 30% of the known production rates are not used. This simulation is repeated 1000 times with randomly chosen locations that are left out. In total 176.715 of 208.000 of the predicted locations were labeled correctly. This robust modelling process is repeated for every new area and is proven a key contributor for precise Sweet spot prediction.

Validated Database

For sweet spot identification, over the last two years, a detailed DNA database of microbial genetic fingerprints has been generated which can be associated with the presence or absence of sweet spots. Six plays in US are extensively sampled, with different characteristics on productivity, age of the producing interval, type of play (oil vs gas), geology and climate and soil type:

  1. The Haynesville Shale LA area: at the start of the sample period (2013) the highest shale gas producer. Hot and moist climate (bayous).
  2. The Bakken Shale: at the start of the sample period (2013) the highest shale oil producer. Land climate with limited vegetation (prairies).
  3. The Antrim Shale: one of the oldest shale gas producers and also a (proven) biogenic shale play. Situated in forested areas.
  4. Avalon and Bone Spring NM area. Desert environment.
  5. Lewis Shale. Best producer in the Rocky Mountain province.
  6. Big Sandy. Good gas producer in the North East.


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