Utilizing artificial intelligence for early detection in geological, chemical, and biological systems remains a struggle for multiple reasons.
- There are limited examples of events. This results in too little data to train a model.
- There is no clear indication before an event or state change. Interpretation isn't achievable with statistical models.
- Significant delay between a cause and the resulting effect prevents models from seeing correlation. This is critical due to the catalytic properties present in nature.
- Probabilistic answers aren’t sufficient. Deterministic answers are needed to forewarn of events where lives or significant dollars are at risk.
Traditional machine learning requires big data. But our approach doesn’t have that restriction. We mesh domain expert hypotheses with available data to provide more robust conclusions.
Instead of estimating semi-reliable probabilities and accepting the remaining risk, we created a better solution.
Two of the top five oil companies worldwide are Senslytics pilot customers.
Avoid fluid sample contamination and excessively long jobs during wireline formation tests.
Mudgas Reservoir Estimation
Move mudgas logging estimations closer to ground truth for GOR, viscosity, API gravity, and net pay thickness.
Identify areas of accelerated corrosion growth early to increase asset run time and longevity.
Senslytics is the leader of lead time, empowering domain experts and engineers to make decisions with accurate interpretations of complex situations.
Senslytics’ Intuition AI platform is charting new territory in causation-based artificial intelligence, changing the capabilities of early warning systems.
"This tool is going to be very valuable to the Field Engineers who are involved in Wireline Testing. It is also an important step forward in digitizing deep-sea operations."
"We recently gave Senslytics a Positive Lux Take due to its technical value and strong competitive positioning."
"Senslytics is one of the most promising Oil & Gas startups of the year."
Rice Alliance of Technology & Entrepreneurship