Quantum computing is likely to revolutionize how supply chains are designed, managed and optimized. For every hour it takes a classical computer to run optimization algorithms, quantum computing can cut the time to low single-digit minutes.
For classical computers, the “bit” is either a 0 or 1, but in quantum computing the basic unitary structure is the “qubit”. Freed of binary constraints, the qubit can be 0 and 1 at the same time, have negative values and hold much more complex information.
Quantum computing is among several disruptive technologies expected to usher in the “5th generation” of computing. In some cases it could enable speeds up to 100 million times faster than is possible with classical computing.
Current constraints leave difficult oil and gas problems unresolved
The oil and gas industry is full of tough problems (e.g. complex production and transportation arrays). Parallel processing and classical computing fall short in being able to optimize oil-rig operations, such as increasing production while applying safety-related issues and other constraints.
The more variables and observations, the less likely it is for today’s computers to analyze the data promptly and optimize. Current constraints are leaving hydrocarbons underground and billions of dollars on the table.
Oil rigs are equipped with tens of thousands of sensors (about 30,000), generating about 1.5 terabytes of data (the equivalent of downloading 428,571 mp3 songs) each day. Current technologies analyze a mere 1 percent of the data, which is used primarily to detect and control anomalies. Most data is time-sensitive since platform production and safety matters greatly in real time. Massive potential – for optimization, predictive and prescriptive analytics – is largely left untapped.
Experimenting with quantum
Let’s think boldly about applying the power of quantum computing to solve complex challenges in oil and gas supply chains. Enterprises can start by identifying potential use cases.
Nonconvex optimization, where a graph curves up and down, is a strong candidate. While algorithms on classical computers use iterative methods to arrive at optimal solutions, quantum algorithms approach the problem through an entirely different, more physical process.
The ability to access a growing set of software platforms helps enable companies to deploy quantum-based optimization more quickly, and for machine-learning pilots to proceed with a test, learn and iterative approach.
Accenture has started a collaboration with 1Qbit to develop a hardware-agnostic, cloud-based platform that allows companies to take advantage of quantum computing. i Experiments are being designed with clients to:
Discover viable problems using a select set of pre-programmed quantum algorithms
Determine if the algorithms are adequate replacements for classical computing implementations
Develop a quantum application to demonstrate functionality and potential benefits
Quantum’s potential is being explored across industries, including pharmaceuticals, where it can take a decade to bring new drugs to market. In a proof of concept for Biogen, Accenture has demonstrated the quantum-enabled method for molecular comparison was as good or better than existing methods. i i Using quantum computing on the front end could dramatically speed time to market, repurpose pre-approved drugs more easily, and empower computational chemists to help make discoveries faster.
Mass adoption is only a matter of time as quantum-computing hardware scales to functional use and facilitates costs decline. Enterprises that move ahead now with experimentation will be prepared to capitalize on quantum opportunities for performance breakthroughs.