Why Biosurveillance

The benefits of using microbes as sensors and tracers

Microbial DNA analysis is a widely available commercial diagnostic for the energy industry, with its origins in monitoring microbially influenced corrosion (MIC) or H2S development via sulfate reducing bacteria (SRB). 

In practice, microbes are readily extractable from produced fluid samples owing to the typically high concentration of microbes (high biomass). However, the use of DNA from rock samples like well cuttings and cores is substantially more difficult due sample contamination and the very low concentration of microbes (low biomass) in those samples.

DNA Diagnostics Benefits

Enhancing fluid movement diagnostics

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Total Fluid Analysis

Total fluid movement of combined oil and water

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4D Application

Long-term monitoring with no sample storage

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Sustainability

Environmentally safe and friendly; low carbon footprint

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Low Risk

Non-disruptive to well operations; no shutdown time, lost production or deployment of donwhole tools

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High Resolution

Unique fluid profiling by characterizing well cuttings and produced fluid

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Integrated Data

Analysis integrated with type curves, logs, completion designs and operational events

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Scalability

Field-level analysis with 2 week turnaround on fluid results

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Affordability

A fraction of the cost of other diagnostics and long term monitoring

The Biota Difference

Sample Stabilization

Biota’s proprietary Standard Operating Procedures (SOPs) to capture cuttings and fluid samples reflect the extensive experience of having deployed the technology on 1,400+ wells in a broad range of operating environments. 

While cold storage and shipping of samples is commonly used, advanced sample stabilization methods are available for sample preservation.

Low Biomass Extraction, Sequencing, and QA/QC

Low biomass cuttings samples can harbor microbial biomass on the order of 50-100 genomes, and reagent microbes can dominate the downstream DNA marker sequences. 

The sequencing of negative extraction controls (NEC) allows for the identification of microbes that have metabolisms incompatible with the extreme subsurface environments. These reagent microbes can be dropped from samples computationally before performing downstream analysis.

Reliability and Scalability

Our proven lab processes have demonstrated to reliably recover high quality signals from a broad range of operating environments and types of environmental samples. Our high throughput extraction and sequencing workflows combined with the automated data science pipeline provides the ease of scalability.

Technology Foundation

Microbes are descriptive of their environment and can be uses as sensors and tracers.

DNA Subsurface Signature

Microbes are present in the subsurface and exploit local variations in physical and chemical conditions and therefore are very highly associated with specific local subsurface intervals. These differences in microbial communities are brought to light by Biota. We analyze extracted microbial DNA sequences via proprietary bioinformatics methods. 

We then look at the presence/absence, abundance, diversity, and evolutionary relationships of specific microbes, which are used to create a database of DNA marker sequences that are highly associated with, and therefore are used to define, different subsurface spatial regions spanning the vertical strata and formations as well as horizontally within the same formation along a lateral well.

Subsurface DNA is Ubiquitous and Resilient

Microbes exist in subsurface pore space, even if that is at the micrometer scale, which is typically seen in oil and gas reservoirs and source rocks. Furthermore, microbes can be found in extreme environments such as very high temperatures, and living bacteria can be found in 100M year old formations. (Science, July 2020

From DNA to Diagnostic

Stanford Research at Sanford Underground Research Facility, SD (2019), used technology co-developed by Biota’s technology team. They analyzed formation water samples from new boreholes near mine shafts and used microbial fluid signatures to ID well connectivity from natural fractures. The hypothesis supported by analysis of coring run intersecting wells. 

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