siliconindia | | November 201519Dr. Satyam Priyadarshy, Chief Data Scientist, Halliburton LandmarkBig Data Play in Oil and GasThe oil and gas industry is experiencing multi-dimen-sional landscape changes, including economical, production and consumption areas. The impact of these changes starts with the upstream business also referred to as exploration and production (E&P) industry.The E&P industry is one of the most complex operations among any of the industry verticals. This industry has been at the forefront of massive data collection historically, well before the term Big Data has been in use. The data collected is from instruments, sensors, computer software and hand-written notes for conducting effective and efficient operations. On a daily basis this data collection can range from a few terabytes to a few petabytes, depending upon the phase of oil well life cycle and the complexity and modernity of the oil field. The overarching goal of the E&P industry is to produce maximum oil at the lowest cost possible with the highest degree of safety for all stakeholders. Another important aspect for E&P industry is that the above goal must be achieved within the ever-increasing costly restrictions imposed by the global, regional and local regulatory authorities. Thus, the E&P industry has to remain innovative and competitive at all times. Forward looking E&P companies must adopt Big Data, the second industrial revolution to remain competitive and innovative. The industry has a strong foundation for the seven pillars of Big Data--namely, Volume, Velocity, Variety, Veracity, Virtual, Value and Variability. The meta-data associated with tools used in exploration and drilling could be in few megabytes while the metrics it collects daily could range from megabytes to gigabytes to petabytes, covering a wide range of volume through the lifecycle. The data comes at different velocity, some are collected and processed in batch mode, while some data may be collected in real-time and need for actionable insights to be real-time as well. As mentioned earlier, the data comes in highly structured numerical format to grossly unstructured hand-written reports on an irregular to regular basis, thus the variety of data in E&P covers all types of data including audio, video, text, numerical, etc. The fourth pillar is the veracity commonly referred as the truth in data. For E&P, this is critical pillar because the data that is collected through thousands of sensors is important, requiring regular monitoring, analyzing and recalibration so the metrics remains relevant. The impact of weather, temperature, pressure, fluids and other activities on these sensors could pose challenges for keeping the truth in this data collection. Similarly, the handwritten drilling reports and other structure and unstructured reports must speak to veracity.Additionally, the data in the E&P industry is in multiple locations and due to the mobility gap moving this data is a big challenge, so one has to leverage the virtual pillar of Big Data. The Virtual pillar addresses data duplication and lost in transformation related problems while enabling better data governance.The variability occurs in these five pillars, across the phases of oil well life cycle. For example, the exploration data is generated in terabytes to petabytes but does not need to be analyzed in real-time, hence has low velocity. The seismic analysis is critical for the E&P industry thus has a significant value compared to many other phases of life cycle. During the drilling phase the data may be generated in real-time and requires actions to be taken in real-time for optimal operations, thus the velocity is very high. The last pillar is value. If there is no value in the E&P data then none of these pillars of big data matter much. Figure 1 shows the relative comparison of these pillars. Figure 1­ A relative comparison of 7 pillars of Big Data in E&P industryCXO INSIGHTS
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