Using Analytics in Oil and Gas to Drive Efficiencies

How to Use Automation to Create a More Efficient Oil & Gas Industry
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To learn how the Oil & Gas industry can generate the full value from the large data generation sources within their operations, join Andrew Meyers during his webinar, Using Analytics in Oil & Gas to Drive Efficiencies, live on July 21st at 11 AM/EST.

COVID19: The Unique Fall of Oil & Gas

In the last dozen or so years, the oil and gas industry is now facing a third downturn. The first of three (2008) was financially driven and the second (2014) was a result of over-supply. Both events had the usual industry responses of layoffs, CAPEX cuts, asset sales and a few bankruptcies. After the initial shock, markets found (some) equilibrium and for most it was business as usual. However, this time is different. Demand for crude, natural gas and refined products has severely eroded. There is evidence of recovery although making a case for Pre-COVID19 demand levels and price recovery within the next few years can be rather difficult.

Given the effects of the commodity price environment on the entire value chain, IDC recently commissioned a flash survey among managers and executives in upstream, midstream, downstream and oilfield services. As you would expect from the survey, industry layoffs are inevitably the first industry response to this type of event. Other actions were the usual moves to outsourcing, renegotiating with vendors, changing job roles, etc. What we found interesting is the next most given response across the sectors (aside from layoffs) was “deploy automation more quickly”. Past actions of the industry might make it difficult to imagine a collective digital journey but is there really a choice? In upstream, aside from some of the OPEC nations and Russia, margins will be thin to negative in many producing regions given oil prices. Increased global competition was already putting pressure on downstream and chemicals businesses (IDC Perspective Coronavirus Impacts on the Energy Sector, Mar 2020, Doc# US46167620).

The Power of Analytics

It is time for more resilient decision making in oil and gas. Automation supported by AI/ML is critical to becoming more efficient in the industry. The industry has always been long on data but short on analytics outside of operational silos. As with many industries, the problem is culture and resistance to change. As we embark on a smart oil and gas business, data (cleaned and consistent) and analytics must be de-siloed to support a resilient decision making and automated enterprise.

There are many quick and effective back office RPA concepts that are being deployed to address OPEX and G&A cost pressure that the industry is facing, but I would like to address the industrial automation side of the coin. Oil and gas has always kicked around the idea of analytics-supported autonomous operations, whether that is exploration, drilling, production, repair/maintenance, processes, etc, but didn’t feel particularly incentivized to address the ideas in times of high oil prices and healthy margins. Now there is not only technology available, there is the will and recognition of necessary behavioral change.

The power of analytics has already taken hold in downstream and process functions. Asset Performance Management (APM) and asset analytics are allowing facilities to maximize up-time by recognizing and preventing failures while eliminating unnecessary scheduled inspection and maintenance. This is particularly valuable in a greenfield project where the new equipment is digitized at plant commissioning. Brownfield digital deployments can sometimes run into internal snags when a heap of internal materials and processes need to change if a digitized version of the equipment is installed.

Burdened Pursuit of Production

Ambitions in upstream remain. Since exploration budgets are likely to be suppressed for a few years, let’s take autonomous drilling for example. Operators and drilling contractors alike have wanted to remove personnel from the drillsite. While this has yet to materialize (in any form of scale), support for the idea has always existed as labor costs rise and the race to perfect safety records continues. Much of the analytics are in place to support the development of this type of program, but funding and scaling the operations technology (OT) remains a challenge. Sharing the burden of R&D and production costs has not been a strength of the industry for some time. In a suppressed market, many oilfield manufacturers have reduced new product development budgets to very little, but improved collaboration in the industry could be key to solving the problem.

Several value-additive point solutions are currently being deployed across the value chain and referenced in the publication below. IDC expects further acceleration of enterprise-wide analytics-supported automation will be prevalent in the industry in the next half decade. Higher cost producing regions will have little choice but to make organizational changes and pursue technology (IDC Perspective How Oil Companies Are Using Analytics to Improve Efficiencies, Apr 2020, #Doc # US43345719).

To learn more about the new era of analytical tools and their uses in transforming the Oil & Gas industries, join Andrew Meyers during his webinar, Using Analytics in Oil & Gas to Drive Efficiencies, live on July 21st at 11 AM/EST.

Andrew leads IDC's Worldwide Oil & Gas program, collaborating with global teams, and is responsible for developing and leading IDC's worldwide research on Upstream, Midstream, and Downstream Oil & Gas operations. His core research coverage includes the ongoing and accelerating digital transformation in the Oil & Gas industry. Based on his background covering the energy space, his research also includes a particular emphasis on how digital transformation is changing energy markets and business models in the sector.