Shale Value: Fluid Analysis for Optimizing Shale Asset Value

Shale Value

Pavana Gadde, CEO , Shale ValuePavana Gadde, CEO
The primary objective of shale-focused operators is to optimize well performance and minimize development costs. A good understanding of sub-surface fluid behavior is a key step in accomplishing this goal. This is where a Houston-based shale technology company, Shale Value, can do wonders by providing valuable insight for businesses with limited data. The company integrates cutting-edge fluid analysis knowledge, deep domain reservoir engineering, and machine learning expertise to help clients evaluate and optimize shale and tight oil assets.

In an interview with CIO Applications, Pavana Gadde, CEO, and Phani Gadde, Co-founder, Chief Product and Marketing Officer at Shale Value, share their insights on how they solve the problem of limited fluid data for the shale industry, objectively benchmark acreage and frac performance and optimize fracs. " We focus on the science before embarking on data science by building physics-based models and then applying statistics and machine learning to the model outputs," says Pavana.

Could you give us an overview of Shale Value?

We started Shale Value in 2018. Our approach to combine reservoir science with data science sets us apart from other players in the market. From E&P operators to institutional investors and commodity traders, everyone benefits from our products—Fluid Analysis and Composition Estimation Tool (FACET) and Forecasting through Inferred Reservoir Modeling (FIRM).

FACET is an industry-first ready-to-use fluid analysis tool. It is built by using public domain data to provide play-wide results. The product uniquely converges science and machine learning for detailed fluid analysis for every producing well in any zone. On the other hand, FIRM offers superior benchmarking and forecasting by combining learning from reservoir simulations, analytical models, and our proprietary fluid analysis model through using advanced machine learning. We also provide separator optimization as a service on a consulting basis.

What are the challenges you have observed in the marketplace, and how do you help mitigate those?

Operators lack sufficient data to build machine learning models for achieving critical results to forecast well performance. For example, in the Delaware basin, various operators drill wells across multiple producing horizons, but nobody has enough data to develop robust machine learning models for frac optimization and estimation of fluid properties. This is where we are making a difference by using physics-based models to understand the sub-surface system first, and then applying machine learning to ensure an optimum outcome.

Phani Gadde, Co-founder

Could you give us a customer success story?

In the shale industry, operators need to use fluid properties as engineering inputs to a host of analyses, including reservoir engineering and production engineering. Collecting the fluid samples and analyzing these in a lab often costs $30,000 to $50,000. This lab data needs to be further analyzed to develop fluid models. However, due to the cost pressures, the industry only collects and analyzes fluid data on about one to two percent of the wells that they drill.

We focus on the science before embarking on data science by building physics-based models and applying statistics and machine learning to the model outputs


One of our clients came across a similar quandary as they were planning to collect three to four samples per year. With our model, they could directly plug the end result into their engineering analysis and save about a million dollars over the next few years by eliminating the need to collect and analyze the data.

In another case, we are working on separator optimization. Fluid data is a crucial input for separator optimization. Depending on a separator's condition, some intermediate species can either go into a gas stream or oil stream while separating the oil and gas mixture. Therefore, it requires an extensive understanding of fluid behavior to optimize these separators. We are working with a large operator in the Permian to optimize their separator conditions. As a result, we expect their oil production to increase by 2-5 percent with zero additional capital expenditures (CapEx). “We have observed that E&P operators with enhanced optimization capabilities get the best return on their investment,” says Phani.

How did your clients respond to your products and services so far?

We have received positive feedback as most operators recognize that they can benefit vastly from our products and services and that we are the first in the industry. Previously, they didn't have tools to simplify their work flows without any need to collect fluid samples. Today, they can get fluid analysis with just one click of a button. Our user-friendly and straightforward solutions allow clients to obtain the necessary information any bypass the current elaborate processes. In fact, several clients acknowledge our products and services as the future of fluid analysis.

What does the future look like for the company?

We started Shale Value with an aim to help operators maximize return on investment from shale assets. Given the volatility in the commodity prices, clients want higher returns through optimization. With optimized fracs, operators can improve well productivity and well net present value (NPV) with minimal increases in CapEx. This is why we are focusing on optimization. Our tools primarily bridge the technical and commercial chasm that currently exists in the industry. These tools are sophisticated enough to be used by operators for E&PS workflows and deliver commercial insights to both investors and operators simultaneously. We can offer this unique analysis due to a distinctive blend of deep domain reservoir engineering and machine learning expertise.

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