Big Data Is a Big Deal

Abstract

Guest editorial The global population is forecast to grow to about 10 billion people by the middle of this century. While this population growth will generate a growth in global GDP, it will also create significant stresses on resources needed to feed the population and fuel its economic growth, with the demand for food-water-energy creating a “stress nexus.”  The Food and Agriculture Organization of the United Nations predicts that by 2030 demand for food will increase by 50%. The International Food Policy Research Institute expects demand for water to increase by 30%. And the International Energy Agency forecasts that energy demand will surge by 50%, despite projected progress in improving consumption efficiencies. Alternative fuels are forecast to find ready markets and increase their percentage of the energy mix, yet oil and gas are still expected to deliver about 60% of the energy needs of the future. For example, in 2040 the exploration and production (E&P) sector is projected to be faced with delivering about 30% more oil production liquids, about 110 million b/d of oil equivalent, than it does today. The E&P industry is expected to find and develop new types of resources through innovations in technology used in deep water, the Arctic, oil sands, tight oil, unconventional gas, biofuels, and other areas. However, two major issues will mute and limit that success: Manpower. As demand increases, the need for manpower increases and manpower availability decreases. Simultaneously, experienced people will retire and exit the industry in record numbers. Data and knowledge. Our current knowledge of existing reservoirs and our practices are based on partial data. It is a truism in the business world that 80% of business-relevant information originates in unstructured forms. In the E&P industry, where “natural data” cannot be ordered and constricted to the confines of “manmade” databases, the percentage of unstructured data can be substantially higher. In the domain of criminal justice, The Innocence Project has shown that partial data can lead to partial truths, in some cases leading to incarceration of innocent people. In many of those cases, DNA evidence not considered in earlier jury trials has exonerated innocent people who spent decades in prisons. Partial data can lead to partial truths. The E&P industry has had success working with partial data and partial truths but it is imperative that it work with more and better data, or “Big Data,” to get closer to the whole truth, and to ensure greater success so vital to meet projected future demand of a growing global population. Both challenges mentioned above could be met by focusing attention on creating a unified data store that is a ready platform to apply computational algorithms and analytics to extract patterns from both structured and unstructured data. These patterns can then be used to create models with forecasting, anticipatory, or predictive capabilities that reduce the cones of uncertainty or increase the probabilities of success of actions in the E&P industry.