Big Data in Oil & Gas Industry

For Petroleum Industries, finding and producing hydrocarbons is challenging and economically risky. The processes and decisions related to oil and natural gas exploration and production generate large amount of data. Industries require new technologies to integrate and interpret data to make better decision which in turn reduces environment impact and increases recovery rate. With new data acquisition, processing and storage solutions, new devices required to track an array of reservoir, machinery and personnel performance are developed. The data is projected to double in two years.

The integration and mining of data produced in the hydrocarbon finding and producing process offers answer for some of the biggest questions faced in the oil industry. The biggest question: Where is more oil? How do we get substantially more out of the ground safely, with minimal environmental impact?? 

Geologists and petrophysicists use data that indicates the type of rock in nearby wells, as well as seismic data, produced by sending sound waves deep into the subsurface which bounce back to receivers, for locating oil . The data collected from wells has higher resolution but is accurate for only a small area (10 feet) around the well, so data interpretation techniques are used to extrapolate between wells. This requires scientists to insert considerable “interpretation” into the analysis. The improvement in finding new deposits of oil and gas have occurred through the combination of geology, petrophysics and geophysics, ultimately developing better models of the Earth’s subsurface. The 3D seismic data vastly improves the picture of the Earth’s subsurface and removes the need to drill a multi-million dollar hole, with very little data, to “explore” what is in the rock.

One raw seismic dataset is usually in the hundreds of gigabytes, resulting in terabytes once processing and interpretations are finished. These processing algorithms calculate many billions of data points with each run, and hundreds of these runs occur globally every day in order to create a clear, accurate picture of the Earth’s subsurface and to identify all of the major components of the hydrocarbon systems.

The oil and gas industry can learn much from the data, yet it is generally used the same way it was historically used. Typically, the data is gathered and stored in different databases, file cabinets and various geoscientists’ and engineers’ desks. Grains of similar rock behave the same everywhere else on Earth. While they are never laid down the exact same way, the lessons learned in one area could be extrapolated or applied to another area. Today, this process is very manual and labor intensive. 

Data science will help the oil and gas industry learn more about each subsystem and make an accurate decision, ultimately reducing risk. Big data analytics will be key. While the concept is still in its infancy as far as the oil and gas industry is concerned, here are some possible near-term big data analytical solutions:

·         Integration over a wide variety of large data volumes – incorporating all relevant information for finding additional hydrocarbons, and identifying the data and the best known technologies to produce it – for that particular system.

·         Make daily operational data relevant to reduce operating costs and improve recovery rate.

·         Decision management – take into consideration all conditions and quickly identify if or how to proceed.

Other industries are embracing big data analytics, but the oil and gas industry is just now getting the concept to make decisions. When it comes to production, the digital oil well, oil field and data formatting standards have led to operators putting gauges and data gathering devices on everything possible in the field. Capturing this data allows very large fields to be managed from a “central command center” rather than by people physically checking every well. In a field with thousands of wells, where one person once checked five to 10 wells per day, personnel costs and the cost of optimizing production have been vastly reduced while production has increased.

Apart from capturing and viewing the data, large number of decision has to be undertaken by an experienced professional. Smarter solutions, with built-in intelligence, using computers has to be developed in order to make complex decisions. The oil and gas industry is ripe for big data analytics, through new software, data handling solutions or data manipulation tools. The primary focus areas should be finding it, producing it and operations.

Reference:   http://viewer.zmags.com/publication/90ffcc6b#/90ffcc6b/21  (Page 20-24)