Managing Cost During Turbulent Times: The Untapped Potential of Data Analytics for Energy Operators

The upstream oil and gas industry is facing another tough year as it looks to manage weakening economic growth and intensifying trade tensions against the backdrop of the energy transition. As a result of this stark market uncertainty, energy operators are increasingly focused on managing their costs. During this period, the progress that many had made on digital transformation projects should not be deprioritised. In fact, better management and analysis of the vast swathes of data at their disposal could help energy operators capitalise on the upturn when it arrives.

Energy operators have access to enormous amounts of data through data subscriptions, e-mailed reports, and internal company repositories. But how are they storing, consuming and disseminating this data within their company? The simple answer is that the data is often so siloed within specific business units or disciplines that many are not. Data is often left collecting dust in unused databases, on hard drives or shared file systems.

In today's climate, operators are focused instead on managing productivity and cost. For example, where are my best producing wells and my worst? Where can we focus our best efforts toward enhancing production or shutting in? This is an important focus. Yet, consolidated, detailed information that could potentially help reduce the time taken to complete these types of activities, for example, in this instance, analysis of well performance for field management, is often not easily accessed or analysed.

When analysing operated well production in one or more leases, data must be gathered from drilling, production economics, geoscience, land and financial systems. Extracting and consolidating these disparate sets of data into meaningful information may take days or even weeks. Comparing this with partner or competitive holdings just multiplies the data gathering process. How do operators gauge the completeness and accuracy of the gathered data to perform the best analysis?

One of the largest barriers to accomplishing this task - especially for the smaller operators - is resource. Often, they don't have the manpower to focus on finding and managing the data. In addition, expensive resources are required to focus on data loading and search, not data intelligence.

Leveraging centralized technology to automate much of the data gathering, conditioning, alignment and distribution allows existing resources to be more productive by removing the manual efforts currently involved in these processes.

Automation of data loading and quality control immediately exposes data anomalies and provides a platform to correct values. In addition, having an automated hub, provides one location to find and distribute the most critical data assets to any available analytics platform. Leveraging centralized, conditioned data in analytics platforms allows users to make quicker and better decisions regarding where to spend or save capital.

With the growth in cloud technology, the option to outsource these data management processes through a managed service enables further cost and resource savings. The cloud also offers the possibility of scaling activity up or down, allowing operators to quickly react to the changing business environment.

It's a tough time for the industry when operators are focused - quite rightly - on managing cost. However, investment in data management and analytics, delivered as a managed service, as part of a wider digital transformation program could help deliver valuable insights and reduce cost even further over the long-term. In taking this approach, operators may well find themselves in a stronger position post-downturn to capitalise on the opportunities that will no doubt arise.

Posted 02 July 2020 by Nathan Amery, Executive Director, Global Practice Head, EDM for Energy, S&P Global

This article was published by S&P Global Commodity Insights and not by S&P Global Ratings, which is a separately managed division of S&P Global.