Biodentify utilizes soil sampling and bacterial DNA analysis combined with machine learning to create predictive maps that identify high-potential drilling sites for oil and gas. This technology significantly reduces drilling risks and costs by accurately delineating productive reservoirs and minimizing the environmental impact of exploration activities.
Funding
$2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Exploration and drilling for oil and gas resources is a high-risk, capital-intensive process, often relying on imprecise geological surveys and seismic exploration techniques. Traditional methods struggle to accurately predict reservoir productivity, leading to dry wells, wasted investment, and unnecessary environmental impact.
Solution
Biodentify employs a patented workflow that combines soil sampling, bacterial DNA analysis, and machine learning to generate predictive maps of subsurface hydrocarbon reservoirs. The process involves collecting soil samples, extracting and analyzing bacterial DNA to identify hydrocarbon-metabolizing species, and correlating the data with known reservoir characteristics using machine-learning algorithms. This approach enables operators to accurately delineate productive zones, rank prospects based on their potential, and optimize drilling locations. By identifying high-potential drilling sites, Biodentify reduces the risk of drilling unproductive wells, maximizes financial returns, and minimizes the environmental footprint of exploration activities.
Target Audience
The primary customers are oil and gas exploration and production companies (E&P) operating in conventional onshore, unconventional shale, and offshore environments.
Features
- Soil sampling methodology for collecting representative samples of subsurface microbial communities.
- Proprietary DNA extraction and analysis techniques to identify and quantify hydrocarbon-metabolizing bacteria.
- Machine-learning algorithms trained on a database of known samples to correlate microbial signatures with reservoir properties.
- Predictive mapping that delineates productive zones and ranks prospects based on probability of success (PoS).
- Delineation services for conventional onshore prospects, enabling accurate reservoir mapping.
- Productivity mapping for unconventional shale plays, pinpointing high-producing areas.
- Prospect ranking for offshore wells, enabling operators to prioritize drilling targets.