Dr Nick Coles, director of conferences at Dome Exhibitions, looks at how digital oil fields will help the region to raise its production levels.
The goal of the modern integrated digital oilfield (DOF) is to use real time operational field data in an ever evolving cycle of production analysis and optimisation and detailed reservoir modeling to work towards improving reservoir recovery rates.
It has been reported that the totally integrated digital oilfield is the holy grail for the industry and the focus of the upcoming Abu Dhabi International Digital Oilfield Conference (IDOC 2014, www.idoc-uae.com) will be to discuss the latest developments with this integrated approach. As such this event, hosted by ADNOC will be a first for the region.
The integrated DOF approach includes implementing visualization environments to improve asset team collaboration in a collaborative working environment (CWE); improving productivity using workflows and appropriate software tools; automating processes so as to predict production problems and in turn reduce operational costs and enhancing well production by matching with well potential.
The CWE is enabled by better automatic plant control, which in turn is enabled by better control and instrumentation. Safe and stable operation will not be achieved and deferment will not be avoided unless a solid automation foundation is built for the CWE.
Similarly the latest technologies and current challenges in the areas of real time Integrity monitoring, safety & security and “smart” logistics are of vital importance. These challenges that exist are not only in technology, but also in how to integrate the new technology capability into the work management systems and the ERP and logistics infrastructure and work practices.
The oil and gas industry is now slowly moving from a reactive mode of operations to a predictive and proactive operating environment. Asset teams are being provided with the capabilities to continuously detect, diagnose, and remedy production problems and improve operational performance.
With large number of oil and gas fields becoming mature, the focus on integrated operations has to shift from data integration and visualization to detailed analysis and optimization, enabling the determination of the root causes of problems. Once the problem is identified, it should be a relatively simple next step to prompt engineers with suggested solutions, or even close the loop and fix the problem automatically thus providing real operational smartness .
The drive towards predicting performance and responding to events before they become critical can be applied across most field operations. One of the most advanced areas is in the surveillance of rotating equipment and, in particular, gas compressors. Failures can be catastrophic and the incentive to keep equipment running is enormous.
Artificial lift systems, due their operational complexity, are also prime candidates.
Early detection of Electrical Submersible Systems (ESP), problems can prolong pump life and allow optimal planning of the pump replacement. Other examples that would benefit from predictive diagnostics include the prediction of liquid loading in gas wells the prediction of hydrate production or terrain induced/ hydrodynamic slugging in wells and pipelines and even a prediction of changes to system capacities which could results in production targets being missed.
Historically here the DOF concept has usually been limited to well and surface optimization workflows, attempting to solve production operation issues and asset availability issues. Movement into coupling of the surface to the subsurface is the next logic step in the DOF domain and a feature of IDOC 2014 will be a detailed examination at real world examples of where such practices are being used or contemplated.
Although the timeframes may be different there are requirements to engage a multi-discipline solution considering the overall productivity of the reservoir. Extension of DOF into the reservoir allows faster collaboration and quicker turnaround times for analysis and decision making as the data is vetted and transmitted to the models directly and more frequently.
Being able to visualize well and reservoir performance data, alongside static geologic models and to confirm the simulation models quicker is beneficial. Use of surrogate, data trained reservoir models or subsets of the entire model can introduce faster collaborative methods to optimize reservoir performance and presentations will illuminate the benefits.
Typically reservoir recovery rates at best have been any ware between 35 and 50% and it is the expectation that in observing and employing integrated DOF practices they will contribute to targeting recovery rates of 70%.
Inherent in this complete approach is the vast amount of data generated and the very real need to compare the live data with historic database information, which, again, is costly and time consuming. Another feature of IDOC 2014 will be the pre-conference workshop that takes an in depth practical approach on how to get extra value from a DOF data historian.
