Technological advances are a constant in E&P, and IT teams must continually incorporate new applications and hardware to support discovery, development and production.
E&P companies are pursuing hard-to-find resources while also using enhanced oil recovery techniques to extend production in mature wells. They gain business advantage by applying the most powerful analytical tools to immense datasets that grow in size and complexity every year.
Technologies such as 3D virtual reality enable geoscientists to see what is happening inside a reservoir and how conditions are changing, often in real time. In exploration, live data from vessels and equipment sensors merges with historical data to support accurate analysis and agile decision-making. Production teams likewise rely on continuous, complex data from remote sensors to support applications that optimize production.
There is a high premium on efficiency and accuracy. When data science and predictive analytics improve the team’s sense of certainty, organizations can move quickly and make sound choices. They can extract crude, gas and NGLs efficiently and avoid cost blowouts in a time when commodity prices remain uncertain.
CIOs are tasked with building out highly complex data warehouses and application sets and delivering them with high performance and availability, all while facing spending constraints of their own. IT needs to choose tools that support scale and integrate more data while managing complexity.
Here is a brief overview of the complex challenges and opportunities facing IT in 2017 and beyond.
Adding storage. As E&P adopts new methods and technologies for analysis, petabytes of new data are reaching servers and feeding geostatistical analysis applications. Applications are delivering high-quality resolution and updating frequently by merging live and historical data. The IT challenges begin with providing the massive capacity needed to receive and store the data and then throughput it to applications that may be running in remote locations. Decision makers need to find solutions that deliver primary storage for interpretation and modeling applications while running a secondary tier where support data is available as needed.
Integrating data sources. Digital transformation is not new to E&P, yet there is important historical data buried in legacy systems that must be integrated to support decision makers. At the same time, live data is arriving in huge quantities from sensors on drill bits, and applications are accessing shared, virtualized well data from third-party sources. Mergers bring new systems on board that that must be integrated without unnecessary complications. The data science challenges are profound. Organizations that can integrate diverse data types and build modernized data warehouses can deliver a huge competitive edge. Geoscientists can enjoy a unified view into reservoirs with rich historical perspective and gain confidence to make difficult decisions that increase productivity and minimize costly mistakes.
Supporting applications. Geoscientists need the latest applications to maintain their edge. The top organizations are moving to 3D virtual reality and ever more complex versions of simulation and modeling to support discovery. In deep sea, acoustic equipment deployed from multiple ships is creating high-resolution maps to discover new reservoirs. Once production begins, time-lapse seismic analysis reveals reservoir behavior, giving engineers the data they need to optimize production. Applications like these need continuous access to massive quantities of data with enormous throughput, often in remote locations. IT needs to optimize storage and file systems to ensure data availability and throughput to support rapid increases in processing power and speed.
Improving scalability. Intelligent file systems that can manage massive capacity and data migrations within a single volume are essential. Geoscientists can best utilize massive pools of structured and unstructured data only when IT succeeds in integrating vast libraries in a converged infrastructure that supports huge scale.
Reducing system complexity. E&P systems are growing ever more complex, and it is important for IT to adapt tools and strategies for handling diverse data types and meeting extreme demands. Maintenance itself can become overwhelming, leaving no resources to focus on productivity. By eliminating silos and implementing automatic load balancing tools, IT can deliver the reliability, throughput and speed that geoscientific applications require.
Reducing downtime. Powerful applications and massive data pools are useful only when they are available and data is not lost. E&P will benefit from availability and replication solutions that protect data and applications and eliminate costly downtime.
Reducing costs. Performance expectations are high, but cost constraints can be severe. CIOs can leverage available tools to promote efficiencies across the organization while also optimizing use of IT resources.
Improving talent. The organization can derive its greatest business value from complex technology deployments by improving technical skills in IT and within user groups. CIOs can work with leadership to prioritize technical competence throughout the company.
By John MacKenna, Energy Writer