Oliasoft´s position on digital infrastructure & eco-systems in the oil & gas industry

In today's rapidly evolving energy industry, enabling a digital ecosystem demands modern software designed for openness, communication, and the free flow of data. It is imperative that data be available and accessible to every application and user precisely when needed. Moreover, the entire ecosystem must be cloud-based to ensure seamless integration and functionality.

The Layers in a Fully Automated Digital Eco-System

Currently, the oil & gas industry relies on outdated systems that confine data to silos, necessitating manual data entry to update engineering calculations required by third-party applications. Until the industry liberates its data, achieving a fully automated digital ecosystem remains a distant goal.

Liberating data in the energy industry is no trivial task. However, several robust initiatives are propelling the industry in the right direction. The emerging digital ecosystem is characterized by open, flexible, and integrated applications that are essential to enabling fully automated workflows. This transformation is illustrated through a structured digital ecosystem designed to liberate data.

Bottom layer: Hosting and Storage of Data

At the core of the digital ecosystem lie cloud services. The cloud serves as the platform where data and applications are hosted, ensuring they are available for use at any time. Leading this space are the three largest cloud platform providers: Microsoft Azure, Amazon Web Services, and Google Cloud.

One critical component of the cloud platform is the orchestration layer, also known as a data lake. Specifically designed for the energy industry, the data lake holds both data models and data for the entire value chain. Domain applications within Geology & Geophysics (G&G) and Drilling & Well (D&W) can store and retrieve necessary data from the data lake as needed. These applications in the data lake layer standardize and clean up data, making it available for other applications.

Mid-layer: Engineering applications

The Value Chain layer is comprised of calculation engines, simulators, and modeling engines. This layer houses the niche software applications that perform domain-specific tasks within energy companies' workflows. These highly specialized applications are developed through collaboration between domain experts and software engineers. Data generated by these applications can either be stored within the applications themselves or in the Data Lake layer, depending on the specific needs of the company. Regardless of storage location, all operations run on top of the Cloud Platform.

Top layer: A future with Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) represent the pinnacle of the digital ecosystem. Once the ecosystem is complete, with data freely available and accessible, AI and ML will become invaluable tools for optimizing business operations. Until then, AI and ML will serve niche areas and be useful in specific use cases.

Integrating Workflows for Enhanced Efficiency and Sustainability

To create value and maximize profit from the Value Chain layer, energy companies will implement their own work processes and adapt the software to fit their organizational needs, thus forming the Data and Workflow layer. 

At this stage, the Digital Ecosystem integrates all moving parts into one cohesive value chain, enabling new use-cases with updated and improved business logic. 

This integration facilitates automation and autonomous operations that are not only safer and more cost-efficient but also reduce the environmental footprint.

Driving the Future of Energy with Digital Transformation

Our team at Oliasoft takes pride in delivering central components that form the backbone of this ecosystem. It's inspiring to witness the rapid adoption of these solutions and see how our work catalyzes companies to achieve their broader visions. 

We help drive the industry's digital transformation, ensuring it remains at the forefront of technological innovation.