Large-scale Reservoir Simulation
a report by Ali H Dogru
Chief Technologist, Computational Modeling Technology Team, Saudi Aramco Exploration and Petroleum Engineering Center – Advanced Research Center (EXPEC – ARC)
The world’s largest oilfields are located in the Middle East. These reservoirs typically have a low annual withdrawal rate and some of them have been in production for decades. During this time, very detailed field and laboratory measurements have been collected. These, together with a comprehensive on-going reservoir surveillance programme, have provided us with invaluable data to construct credible geological models for reservoir performance analyses.
Saudi Aramco uses reservoir simulation technology to manage its vast hydrocarbon reservoirs and relied almost entirely on commercial simulators until 2000. To that date the company used highly upscaled reservoir simulation models. The number of cells was in the range of thousands. We will call this period (1980–2000) the ‘kilo-cell simulation’ period. In this period the simulation model size grew from 10,000 to 150,000 cells. The cell sizes were in the order of 0.5–1km areally. In the vertical direction 10–20 layers were used to represent thick formations in the order of 45–120m.
In 2000, with the introduction of Saudi Aramco’s in-house parallel reservoir simulator, Parallel Oil, Water and Gas Enhanced Reservoir Simulator (POWERS),1
the model size increased to over one million cells.
The average grid cell size was <0.25km, with a minimum of approximately 0.08km (80m). The number of vertical layers also increased from 10 to 100. These high-resolution models were used in large reservoirs, and it was proved to be more successful for locating bypassed oil and guiding engineers to drill in specified locations to recover more oil.1,2
period is the ‘mega-cell simulation’ period and proved two important points: parallel computing can be used in reservoir simulation; and high-resolution models in the order of millions of cells can run fast.
One of the major POWERS milestones achieved at Saudi Aramco was in 2002: a 10-million-cell, full-field Ghawar Arab-D simulation model was able to run in one piece for the entire history on a cluster of shared memory computers, and later entirely on a PC cluster. The initial run time for involving 60 years of history and thousands of wells was reduced from 53 hours to a few hours. This period continued until 2010. The model size grew to 30 million cells by the end of this period. Although great success had been achieved, and all of the company models were transferred to the in-house parallel simulator, POWERS, mega-cell simulation technology was still not sufficient to handle gigantic oil reservoirs such as Ghawar or Safaniya with seismic resolution (15–50m areal grid), which require one billion or more cells. Such technology was not available in the industry. Therefore, Saudi Aramco had to also develop the second generation of the parallel simulator POWERS, called GigaPOWERS,3 house, to handle billions of cells with speed.
Benefits of High-resolution Simulation Models With the capability of seismic-scale resolution in the areal direction and log-scale resolution in the vertical direction, the giga-cell simulator can be
© TOUCH BRIEFINGS 2011
used on all the fields that require high-resolution modelling. This capability results in two major benefits: minimised or eliminated upscaling (seismic scale and log scale); and higher numerical solution accuracy due to the smaller grid size. In case of the absence of seismic-scale data to populate the models, high-resolution models with seismic-scale areal grid size still yield better results than coarse-grid simulations. In the following sections we will demonstrate the benefits of fine-grid models. We have generated seismic-scale, fine-grid models by refining the existing mega-cell simulation models. In the future, we expect to populate these models with reservoir properties obtained from seismic or similar measurements such as gravimetric or electromagnetic measurements between the wells.
Benefits of Minimised or Eliminated Upscaling Areal Resolution
This time
Specifically, fluid movement between wells is largely misrepresented by the upscaled models. Although measured properties, such as well pressures, water cuts and gas–oil ratios (GORs), can be matched at wells with the upscaled models, distribution of oil and water within the reservoir (between the wells) cannot be matched with upscaled models unless the reservoir heterogeneity is properly represented in the reservoir model. Figure 1 illustrates a high resolution geographical model with 0.025km (25m) areal grid size describing flow channels (left of Figure), and the upscaled model (flow model) with 0.250km (250m) areal grid size. As shown in the same figure, the flow channels disappear in the upscaled model. Obviously, the upscaled model cannot adequately simulate the fluid flow in channels specifically, and throughout the reservoir in general.
Vertical Resolution
Fine-grid models should have a sufficient number of vertical layers to capture vertical heterogeneity. Ideally, near log-scale layering2
in the order
of one foot would capture vertical heterogeneity; however, together with fine areal grids it increases the computing time. Therefore, in general, proper vertical upscaling can be applied to reduce the total number of vertical layers provided that vertical heterogeneity is preserved. This
on its own, in
Ali H Dogru is Chief Technologist of Computational Modeling Technology at the Exploration and Petroleum Engineering Center – Advanced Research Center (EXPEC ARC). He founded Saudi Aramco’s parallel reservoir simulator Parallel Oil, Water and Gas Enhanced Reservoir Simulator (POWERS) programme (today’s GigaPOWERS) and is in charge of supervising scientists and engineers developing the programme. He is the recipient of the 2008 Society of Petroleum Engineers (SPE) Reservoir
Description and Dynamics Award and World Oil 2010 Innovative Thinking Award. The project that he leads, GigaPOWERS, won the 2010 Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC) Best Tecnology Award. Dr Ali has a PhD in petroleum engineering with a minor in applied mathematics from the University of Texas, Austin.
E:
Ali.Dogru@
aramco.com
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