We see it all around us today. As supply chain crises have increased, it’s become apparent that the planning and rapid replanning of sourcing, production, and logistics are integral to the stability of our energy supply chain.
This requires a shift from optimizing individual areas of the supply chain, where we analyze diverse actions independently – to an integrated single supply chain, optimized and re-optimized quickly as diverse factors rapidly change due to global events.
The focus must be on speed of response, aka being highly adaptable in our dynamically changing market to assure that we can deliver effectively, at reasonable cost and continued profitability. As we all know, the challenge is that our classical computing systems are reaching their limits.
As data volumes increase geometrically, and the interdependence of our supply chains grows increasingly complex, the computations required to optimize supply chains are outpacing our ability to accurately and efficiently solve them. Especially in the highly compressed timeframes demanded by today’s on-demand and dynamic economy.
Quantum computing is a critical technology for oil and gas companies. That’s because with steadily increasing global demand, optimization becomes more critical. This increased complexity is overwhelming the ability of classical computers to process the optimization computations businesses need. Quantum computing promises to be the answer to this increasing challenge.
Here’s how quantum computing contributes to lower cost and efficient energy delivery while simultaneously maintaining bottom-line results for oil and gas companies.
The Quantum Computing Paradigm Shift for Supply Chain
Quantum computing is an entirely new paradigm for solving complex problems, such as defining the best possible supply chain operations. These complex problems, or computations, require the analysis of extremely large amounts of data to orchestrate the components of intricate supply chain operations. These operations range from planning and sourcing to production and logistics scheduling to assuring deliveries that avoid out-of-gas situations.
Quantum computers are ideally suited for such computations because:
- Predictive and prescriptive analytics are key components of oil and gas optimization computations and simulations. Quantum computing computes and delivers faster, more precise results for these types of computations. They are inherently designed to solve such problems in a way that eliminates the limitations we are experiencing with classical computing today. As a result, they can process more complex information, faster, and deliver a diversity of precise results.
- Optimization algorithms drive these analyses. Different optimization models are applied in various fields, yet the fundamentals remain the same. As the complexity and amount of data involved continues to increase geometrically, and classical computing reaches its limits, we need better ways of solving these problems. Quantum computers deliver a better way.
The graphic below offers an example of how optimization problems scale in a delivery example.
As you can see, the volumes of data scale geometrically as the number of locations for delivery increase. This is one reason classical computers are struggling to solve these critical computations. They are simply too large when they expand to all the potential options that need to be evaluated.
Now let’s look at this data volume in oil and gas. According to Accenture, oil rigs are equipped with about 30,000 sensors, generating 1.5 terabytes of data each day—the equivalent of downloading 428,571 mp3 songs. Only 1 percent of that data is analyzed, leaving massive potential largely untapped.
Scale is where quantum computing comes into its own. Quantum systems solve problems through an entirely different process than classical computers. They process far larger volumes of data, with more complex algorithms that apply a diversity of constraints and goals across all the facets of the oil and gas supply chain.
Additionally, quantum computing delivers a diversity of solutions that meet all the requirements of the stated optimization. Classical systems only identify the single most optimal solution. The one best answer.
We used to assume that was good enough. Not anymore.
Often, an answer that is only different in its results by .0004 may be the better solution given a specific situation. Yet classical systems only deliver one result. Period. Not all the results that match your requirements. Quantum computers deliver all the possible options, ranked by their match to your requirements. This gives business experts the chance to review multiple options to select their best option. It also aids in assuring that the answers are indeed the best possible results, increasing accuracy.
The Bottom Line
Supply chains are growing more and more complicated, and more and more critical. We all understand that now.
Optimization computations are key to the effective and efficient up mid and down stream supply chains. Integrating these tiers into a seamless chain from raw exploration to final consumer delivery increases the complexity and size of these optimization computations,
Today’s classical systems simply can’t keep up with the scale and complexity, much less the constantly accelerated response timeframes, that supply chain optimization demands.
Quantum computers will optimize oil and gas supply chains, beyond any level of efficiency we have ever experienced. Yes, these systems are early generations. Yet their abilities are expanding constantly, and much faster than expected.
Much of what’s needed to make quantum computing ready for prime time is human knowledge. Quantum is the foundation of nature – it works all around us. It’s up to us to expand our understanding to harness the limitless potential of this amazing and powerful new computing paradigm.
And we will.
