Hilcorp Implements Analytics Platform and Cloud Historian

In the competitive landscape of the U.S. oil and gas sector, Hilcorp stands out as the largest privately-held company of its kind. With a business model that is laser-focused on doing more while spending less, Hilcorp’s strategy resonates through every tier of the organization. It’s not just a mantra; it’s an operational blueprint that is integral to the company’s market leadership.

The Challenge

From an operational standpoint, Hilcorp has clearly defined expectations. The company aspires for a unified, centralized platform that integrates all essential operational data, from equipment and well statuses to comprehensive production metrics. This is not just for the sake of efficiency but also to facilitate the rapid assimilation of newly acquired assets. The objective here is twofold: Hilcorp aims for data that is not just voluminous, but high-quality and actionable. This enables the company to elevate production while minimizing downtime, and importantly, doing so in a cost-effective manner. In a capital-intensive industry, avoiding unnecessary expenditures is not an afterthought; it’s a core competency. When it comes to Information Technology, Hilcorp is equally ambitious. The IT department is tasked with deploying a collaborative engineering calculation library and machine learning models at an industrial scale. This ensures that the company remains data-agnostic, enabling it to recycle workflows and thus increase efficiency. Keeping pace with industry best practices, Hilcorp is keen on adopting modern, serverless solutions that are not just reliable but are also streamlined for easy maintenance.

Hilcorp at AWS Re:Invent

About Hilcorp

  • Hilcorp is the largest privately held oil company in the US, by volume.
  • Acquisition based company more than a dozen of (independent) asset teams
  • Multiple SCADA systems
  • 30,000 Wells across 9 states

Project Highlights

  • Ingest and enrich SCADA data at scale
  • Deploy calculations and alerts to the field rapidly
  • Increase base production by identifying wells that need intervention before they go down


The solution that Hilcorp has deployed is a cutting-edge Analytics Platform and Cloud Historian. Built on Amazon Web Services, the platform embodies modernity in every facet. By utilizing EOT’s products and S3 as a time series historian, it offers a serverless environment that eradicates the need for costly infrastructure. The real game-changer here is its unification of production and equipment data into one centralized hub, making the data not just collected but actionable. Equipped with a Machine Learning and Calculation/Alert Library, the platform is not merely versatile but also scalable, capable of running hundreds of calculations. It’s designed to deliver high-quality, actionable insights and recommendations that elevate production metrics. By avoiding any unnecessary components, the solution adheres to the company’s ethos of doing more with less, offering a lean yet robust analytics tool that aligns with both operational and IT objectives.

Learn More About Solutions & Architectures

Industrial Data Lake

An industrial data lake is a large-scale, centralized data repository specifically designed to store, process, and analyze vast amounts of structured and unstructured data originating from various industrial assets, such as machines, sensors, production lines, and control systems. By offering a highly scalable and flexible storage solution, industrial data lakes enable organizations to efficiently manage their operational data and unlock valuable insights that can drive cost savings and revenue growth.

Enterprise Data Historian

A cloud-based enterprise data historian is a specialized data storage and management system designed to collect, store, and analyze time-series data generated by industrial processes, equipment, and control systems, with a particular focus on historical sensor data. By leveraging cloud technology, these data historians provide a highly scalable, cost-effective, and secure solution for storing and processing large volumes of historical and real-time data. The primary objective of a cloud-based enterprise data historian is to help industrial companies make data-driven decisions and optimize their operations using historical sensor data.

Industrial Digital Twin

An industrial digital twin is a virtual representation of a physical asset, process, or system within an industrial setting. It serves as a single source of truth for asset metadata, asset relationships, and hierarchical structures, providing organizations with a comprehensive, up-to-date, and accurate view of their industrial operations. By utilizing real-time data, advanced analytics, and simulation capabilities, digital twins enable organizations to optimize their processes, enhance asset performance, and reduce costs.