Unlock Cost Savings in Fluids Characterization

Fluidsdata is leading the future of fluids characterization by harnessing the power of AI-ML models to deliver precise property predictions. By leveraging our innovative AI-ML models, our clients can reduce fluids sampling costs by 50% and analysis costs by an impressive 80%.

Our proprietary suite of AI-ML solutions integrates cutting-edge artificial intelligence workflows with deep fluid domain expertise, offering oil and gas operators a revolutionary approach to utilize fluid characterization data. With Fluidsdata, clients can maximize the value of existing fluid characterization data, cutting future costs associated with fluid sampling and analysis while optimizing data collection processes for future operations.

Optimize Your Fluids Sampling and Analysis Programs with AI Predictions

Fluids characterization data—such as composition, saturation pressure, viscosity, GOR, and more—plays a vital role in reservoir modeling, reserve estimation, production assurance, and facility design. Fluidsdata’s AI-ML models offer a game-changing solution by predicting these fluid properties with unparalleled accuracy. This is especially beneficial for operators working with multiple wells with similar compositions, no matter their geographic location, where clusters of reservoir fluid compositions can be leveraged for for optimal results.

Rather than defaulting to expensive and time-consuming reservoir fluid sampling and analysis programs, operators can now utilize our AI-ML technology to extract insights from historical data, minimizing the need for fluid characterization tests, and more importantly expensive fluid sampling. If a new fluid closely resembles the fluid composition in the existing cluster on which the AI-ML prediction model has been already developed, there may be no need for additional testing—saving clients up to 80% in costs.

Turn Your Fluids Characterization Data into an Asset

By applying advanced AI-ML techniques, we help reduce the number of required bottomhole and pressurized surface samples by half. This significantly lowers costs and sample volume requirements, streamlining the process for both exploration and producing fields. Fluidsdata’s AI-ML models ensure that you get the most out of your existing data, turning it into a powerful asset for future decision-making.

Combine Fluids Domain Expertise with AI-ML Innovation

At Fluidsdata, we know that true innovation happens when deep fluid domain expertise meets cutting-edge AI-ML technology. Our team’s unique combination of thermodynamics, chemistry, and fluids characterization domain knowledge ensures that our AI-ML models not only deliver accurate predictions but also adhere to the fundamental principles of phase behavior and physics.

While data science can reveal correlations between parameters, not all of these relationships are meaningful. That’s why Fluidsdata’s domain experts had taught themselves AI-ML modeling much before it was cool. Having pioneered fluids characterization property predictions with AI, our team has led the way in applying AI and ML models to fluids and PVT characterization since early 2000's. Our team ensure that only the most relevant and but also scientifically sound correlations are applied in AI-ML modeling. This rigorous approach prevents costly errors and warrants that your fluid property data predictions are reliable and actionable.