Oil and gas production in a digital age

Data is important as it has always been the backbone of the decisionmaking process and the viability of businesses depend on the quality of decisions made. The processes for oil and gas exploration, development and production generate large amounts of data and the volume of this data grows daily. Big Data analytics are expected to be fully utilised by the oil and gas industry in the future. Hopefully, this is a point not loss on all stake holders in this country.

According to a recent Reuter’s report, in today’s US shale fields, tiny sensors attached to production gear harvest data on everything, from pumping pressure, to the heat and rotational speed of drill bits. These sensors are leading Big Oil’s mining of so-called big data, with some firms envisioning billions of dollars in savings over time by avoiding outages, managing supplies and identifying safety hazards. The industry has long used sophisticated technologies to find oil and gas but only recently have oil firms pooled data from across the company for wider operating efficiencies. When oil traded at more than $100 a barrel, data analysis was an “afterthought” for most oil firms. However, with prices at about $47 a barrel, the efficiency aspect is considered far more important.

A 2016 survey by Ernst & Young examined 75 large oil and gas companies and found that 68 percent of them had invested more than $100 million each in data analytics during the past two years. Nearly three quarters of those firms planned to allocate between six and ten percent of their capital budgets to digital technology. Simple sensors already increase safety and savings by eliminating the need to send workers to rigs or production facilities to gather data. Automating drilling decisions can produce more consistent results by cutting out human errors. The driller is now able to focus his attention on the well and the performance and safety of his crews, as opposed to the manual manipulation of controls.

Occidental Petroleum Corp also uses an analytical tool to find the best design for hydraulic fracturing wells. A new version of the software analyses data on well completions and geology to recommend whether injecting steam or water would produce more oil.

Abhishek Gaurav, a petroleum engineer for closely-held Texas Standard Oil, said he uses big-data analytics to help his company choose which properties to explore. Using Spotfire, the same program utilised by Conoco Standard applies a combination of data science and petroleum engineering to rank asking prices for land based on a variety of completion, production and geological variables, such as the amount of sand that likely would be required to complete a well in a given formation. This technique has reduced the time needed for evaluating land parcels from weeks to hours, and resulted in better decisions.

Unfortunately, some of the information needed by oil firms is not very easy to gather or analyse.

Surveys and maps that companies use to acquire acreage for drilling, for instance, are often not digitised.

Older company data on wells may be unstructured or spread among suppliers using different storage formats, making integration and analysis a challenge. General Electric and its oil-and-gas unit are moving aggressively into the business of digitising industrial equipment for other firms, and have invested in large data processing centres for energy clients. GE sees huge potential for market growth: a company study estimated that only three to five percent of oil and gas equipment is connected digitally, and less than one percent of the data collected gets used for decision-making.

Clearly, we are entering a new era of unprecedented data availability, where digital trends are disrupting traditional business models. These trends have enabled the emergence of big data and advanced analytics, which is rapidly becoming a big industry.

There are four key applications that are emerging for big data in oil and gas companies - digital fields, predictive plant and drilling analysis, Remote operations and Reservoir modeling and seismic imaging. Research shows that “big data” can help to reduce costs, improve decision making and operational performance, achieve greater efficiencies and develop new business models with increased market presence and revenue. Assuming our oil and gas producers are at various stages of use of these new techniques our policy makers must examine how best they can contribute to increased efficiency. At the present gas and oil prices, all stake holders should exploit ways of lower costs and ensuring profitability in the oil and gas sector.