The scope of this publication is to capture the main learnings from the application of ensemble-based modelling of three giant geologically complex carbonate reservoirs onshore and offshore Abu Dhabi, simultaneously considering static and dynamic uncertainties. The ability to consider these uncertainties in prediction studies is highlighted, leading to optimal economic decisions to be taken in the subsequent stages of development of these critical assets. For each oilfield, an integrated static-to-simulation modelling workflow was built in collaboration with the relevant asset teams, capturing their knowledge and expertise in the generation of an ensemble of cases, equiprobable and plausible from the point-of-view of geology and dynamic characteristics. Each of them has specific geological and hydrodynamic challenges to be taken into account, from the spatial distribution of the static rock types and of their heterogeneous petrophysical properties, the impact on the flow of high permeability streaks and stylolites, to the behavior of the aquifers. Each ensemble of cases is subsequently utilized to assimilate the production data using an iterative ensemble Kalman method yielding ensembles with the ability to reproduce the observed reservoir dynamics. These calibrated ensembles can subsequently be used for predictions and economic evaluations considering all remaining static and dynamic uncertainties. After data assimilation, the ensembles showed reasonable match to field and well historical data for the three different studies. There were significant learnings in the static and dynamic updates and uncertainty reduction that occurred during the data assimilation. They provided statistical insights with respect to the reservoir characterization, such as increased high permeability streaks probability in specific zones or reduced uncertainty surrounding the porosity/permeability transforms for each rock type, and fluid dynamic, such as fault behavior. These learnings will benefit the team to further their understanding and improve future modelling activities. Multiple development scenarios were considered for each asset and the simulated ensemble results were brought for economic evaluation under static and dynamic uncertainties. This provided representative estimates of the net present value of each scenario and eventually, a complete understanding of the potential outcome, allowing for informed decisions. Finally, another important benefit of working with calibrated ensembles was shown in its ability to identify the most likely bypassed area from a probabilistic standpoint, allowing to take confident decisions for new target identifications to increase the ultimate field recovery. While addressing the future challenges of major carbonate oilfield developments and to ensure an optimal decision-making process, the asset team has to consider the complexity of the underlying geological environment, the dynamics of the fluid in the reservoir and their associated uncertainties. An integrated ensemble-based approach from static to simulation with fast data assimilation and economic evaluation of possible scenarios proved to be key to reach all of these objectives.

The formation of near well-bore scale can have detrimental impact on well production. Pore plugging, restriction in wellbore i.d. and perforation plugging due to scale deposition can sometimes remain undetected over prolonged periods especially when very low water production is evident. To overcome this uncertainty, workers in our industry usually rely solely on scale prediction models to identify the potential of scale occurring. However, rarely is this information utilized further to explicitly quantify the impact of scale deposition on well performance and updated in the reservoir model, allowing better field management to be applied.In general, historical work published on scale prediction analyses have concentrated on identifying the potential of scale formation based on water composition(s) and localized information such as pressure, temperature (thermodynamic), while more recent publications have attempted to capture the kinetics and fluid hydrodynamics involved.Whilst these predictions can be very useful, it remains a challenge to then use the data output to quantify the impact of scale on overall well performance explicitly. Additionally, limiting factors and uncertainties can exacerbate the problem further. Examples are:• Availability of multidisciplinary tools to capture the processes involved • Uncertainty in field data including hydraulic flow units • Uncertainty over which layers bear 'scaling water' • Presence of multiple source of formation damage (e.g. fines migration) • Presence of other factors that can impact well performance (e.g. liquid loading, lifting) • Near-wellbore / formation scaling need not be seen physically This paper presents an overview of a new simulation workflow development to capture the impact of scale formation by coupling the domains of chemistry and reservoir engineering. Reservoir, near wellbore and macro-scale simulation techniques were integrated to evaluate the impact of scale deposition on well performance during the production lifetime.From the concise simulation workflow developed, we show how scale has impacted production in two synthetic wells, and more importantly, to characterize the location of the depositing scale. Initial problems relating to uncertainties in flow unit description and identification of potential layers of water source are highlighted, and the solutions to overcome these uncertainties are discussed. Based on this information, the volume of scale deposited at specific locations are enumerated and converted to wellbore and formation skins. Over time, slow deposition of scale was shown to clog up sections of specific perforation intervals along the well length and near wellbore area. By reverse engineering, the explicit impact of scale deposition on well production over time was quantified.

No abstract

No abstract

The formation of near well-bore scale can have detrimental impact on well production. Pore plugging, restriction in wellbore i.d. and perforation plugging due to scale deposition can sometimes remain undetected over prolonged periods especially when very low water production is evident. To overcome this uncertainty, workers in our industry usually rely solely on scale prediction models to identify the potential of scale occurring. However, rarely is this information utilized further to explicitly quantify the impact of scale deposition on well performance and updated in the reservoir model, allowing better field management to be applied.In general, historical work published on scale prediction analyses have concentrated on identifying the potential of scale formation based on water composition(s) and localized information such as pressure, temperature (thermodynamic), while more recent publications have attempted to capture the kinetics and fluid hydrodynamics involved.Whilst these predictions can be very useful, it remains a challenge to then use the data output to quantify the impact of scale on overall well performance explicitly. Additionally, limiting factors and uncertainties can exacerbate the problem further. Examples are:• Availability of multidisciplinary tools to capture the processes involved • Uncertainty in field data including hydraulic flow units • Uncertainty over which layers bear 'scaling water' • Presence of multiple source of formation damage (e.g. fines migration) • Presence of other factors that can impact well performance (e.g. liquid loading, lifting) • Near-wellbore / formation scaling need not be seen physically This paper presents an overview of a new simulation workflow development to capture the impact of scale formation by coupling the domains of chemistry and reservoir engineering. Reservoir, near wellbore and macro-scale simulation techniques were integrated to evaluate the impact of scale deposition on well performance during the production lifetime.From the concise simulation workflow developed, we show how scale has impacted production in two synthetic wells, and more importantly, to characterize the location of the depositing scale. Initial problems relating to uncertainties in flow unit description and identification of potential layers of water source are highlighted, and the solutions to overcome these uncertainties are discussed. Based on this information, the volume of scale deposited at specific locations are enumerated and converted to wellbore and formation skins. Over time, slow deposition of scale was shown to clog up sections of specific perforation intervals along the well length and near wellbore area. By reverse engineering, the explicit impact of scale deposition on well production over time was quantified.