Oil and gas industry has long dealt with large quantities of data to make technical decisions. To learn what lies below the surface and how to bring it out, energy companies have, for many years, invested in various seismic software, visualization tools and other digital technologies to accomplish the task.With the rise of pervasive computing devices and affordable sensors that collect and transmit data coupled with new analytic tools and advanced storage capabilities, this has opened up more possibilities every year. Oil producers can capture more detailed data in real time at lower costs and from previously inaccessible areas, to improve oilfield and plant performance. This industry is moving into the quest of “extracting more value” from their data.

AceelTeam has been working with various strategic partners (subject matter experts) over the years and has been developing various business analytics for this industry. Some of the key areas this industry is aggressively moving into at this moment are as follows.

Enhanced oil exploration

Seismic monitors generate large amounts of data during oil/gas explorations, which can be used to discover new oil deposits. In addition, weather, soil, and equipment data can be analyzed to predict the success of drilling operations and make more intelligent decisions about drilling sites, thus having a direct impact on cost and revenue.

New oil prospect identification

Oilfield managers need to analyze well data, seismic data, industry news and potentially social media to evaluate potential oilfields. They can also utilize that information to identify optimum oil drilling locations and bid on oil leases.

Seismic trace identification

Big Data Platform can be used to store and process seismic data that can be used to discover seismic trace signatures that were previously overlooked.

Oil Production

Analyzing seismic, drilling and production data is important in order to enhance oil recovery from existing wells. This data can help production engineers figure out when to make changes in the oil reservoir over time, and when to make changes in their oil lifting methods. In addition, big data techniques can be used to forecast oil production at wells. If the forecast does not meet a determined production level for a particular aging well, that well can be remediated.

Equipment Maintenance

In order to identify potential drilling errors or equipment failures, sensor data from equipment (drill heads, down hole sensors, etc.) as well as geological data can be analyzed to predict equipment failure and understand what equipment works best in which environment.

Reservoir Engineering

Oil companies need to integrate real-time data into mechanical earth models (a numerical representation of the geo-mechanical state of the oil reservoir). By doing this, they are able to more accurately predict future oil availability and identify oil reservoirs and reserves. Big Data Platform can help process and analyze real-time data from earth models and help develop a better understanding of the subsurface of the earth to develop safer and more sustainable drilling practices.

Security

Oil and gas companies need to identify events or patterns that could indicate an imminent security threat or cyber- terrorist act in order to keep their personnel, property and equipment safe. Predictive analytics is a central part of identifying patterns that can help detect these threats in advance.