A multifaceted strategy is presented which achieved significant reservoir simulation work flow efficiency gains at an operating company. The components of the strategy, including hardware and software, are detailed, and the relative efficiency gain is quantified with respect to the previous approach. The relative business value achieved by implementing the strategy is discussed. The new strategy improved efficiency by leveraging modern technology to impact those tasks of routine reservoir simulation work flows not directly related to reservoir engineering. This involved changes in three primary areas of the classic simulation routine of pre-processing, processing, and post-processing. A turn-key high-performance computing (HPC) solution for hosting data storage and executing simulation job processing was designed and implemented. A modern state-of-the-art simulator was configured for simulation job processing. An innovative simulation project management technology solution was deployed to organise and drive the reservoir simulation work flows and associated data management. The in-place HPC solution was constrained by the configuration of the compute nodes, lack of a master node, and the storage solution. These were configured inefficiently to the point that the expected gains from fast processing capacity were not realised due to other choke points in the compute processing and network. To realise the full potential of fast processing in a modern parallel environment, a custom HPC solution was designed. The custom solution allowed for better communication between the compute nodes and the storage, and incorporated an integrated master node. Next, simulation jobs were configured to run on a modern state-of-the-art simulator optimised for advanced HPC hardware. The new simulator significantly reduced model run times. Lastly, an innovative simulation project management technology was deployed on the reservoir engineer workstations. This technology allowed the engineers to reduce the time spent managing data, and to increase the time spent engineering. The preand post-processing engineering tasks were also made more efficient with the technology. The net result of the new strategy was to increase simulation throughput eight times. The higher volume of throughput led to more optimised engineering solutions and eventually allowed for the development of more complex simulation models. The multifaceted strategy to improve reservoir simulation work flow efficiency combines optimisation of the hardware and selecting software technologies conducive to modern HPC environments to allow engineers to focus the majority of their efforts on engineering rather than on systems and data management.

The western area of Abu Dhabi's Late Jurassic Arab Formation is a huge ultra-sour gas reservoir with an areal gradient in composition. Early on, the data suggested a trend in H2S concentrations along the axis of the field with a sour gas entering from the southwest and migrating to the northeast. This sour gas contaminated the existing reservoir fluid and created the current areal gradient. Gas properties also varied, and in particular, dew point pressure. This paper describes the innovative methodology used by ADNOC Sour Gas to input the varying compositions into the simulation model. The methodology consists of two major steps. In the first, PVT data was analyzed and correlations between H2S and other components were established. The second step involved using PETREL to create compositional maps. Ultimately each grid block was assigned a unique composition based on the H2S concentration at that location resulting in a continuously varying compositional gradient. Concentrations of other components were assigned based on the H2S concentration. The result was a dynamic model which duplicates the areal distribution in composition and accurately predicts the varying dew point pressures using a single Equation of State. Simulation predictions of condensate and sulfur production has been verified by actual plant yields. Four years of production has shown the veracity of the initialization of the composition in the model as no modifications to the original compositional distribution was required.

This paper describes how the reservoir team at ADNOC Sour Gas developed the ability to dynamically adjust and manage their production strategy based on plant product output and market requirements, driving profitability and maximizing value of the sour gas assets of the UAE. The reservoir team developed and successfully implemented an extensive data acquisition program, enabling adequate characterization of a giant ultra-sour gas carbonate reservoir in the Late Jurassic Arab Formation in the western area of Abu Dhabi. The field is located in the southern part of UAE, in the Liwa province, and covers an area of 57 km2. It consists of four main reservoir zones: Arab A, Arab B, Arab C, and Arab D. Current development is focused on the central part of the field with most of the wells dedicated to Arab C. Future development plans will focus on the southern and northern areas of the field. Early during the appraisal stage, the data suggested the existence of an areal gradient in composition across the reservoir. As such, a clear understanding of this areal distribution in addition to the usual reservoir gas composition, properties and behavior was essential in optimizing field production and maximizing value. Over the course of field development, reservoir fluids from different well locations were sampled and analyzed. Various issues were encountered during this process including H2S stripping in down hole samples, contamination from stimulation fluids and quality assurance and quality control concerns in lab measurements. Resolving these issues allowed a coherent understanding of the compositional variation in the Arab Formations. To properly model the compositional variation, an innovative methodology was implemented by the team to initialize the dynamic model. The methodology consisted of two major steps. Firstly, PVT data was analyzed and correlations between H2S and other components were developed. Secondly, through PETREL, compositional maps were created. Ultimately, each grid block was assigned a unique composition honoring the areal variation in composition across each reservoir zone. In addition, empirical correlations between fluid components and plant product streams were developed through material balance analysis. Using product models, these correlations were input into the dynamic model which allowed estimated plant products to be output directly from simulation runs. Simulation forecasts of estimated plant products were later verified by actual plant yields, giving confidence in the methodology implemented. Further, this method allowed a quick turnaround in production planning and optimization thereby reducing the reliance on a fully-fledged plant simulator for short term gains and quick wins.

This paper describes how the reservoir team at ADNOC Sour Gas developed the ability to dynamically adjust and manage their production strategy based on plant product output and market requirements, driving profitability and maximizing value of the sour gas assets of the UAE. The reservoir team developed and successfully implemented an extensive data acquisition program, enabling adequate characterization of a giant ultra-sour gas carbonate reservoir in the Late Jurassic Arab Formation in the western area of Abu Dhabi. The field is located in the southern part of UAE, in the Liwa province, and covers an area of 57 km2. It consists of four main reservoir zones: Arab A, Arab B, Arab C, and Arab D. Current development is focused on the central part of the field with most of the wells dedicated to Arab C. Future development plans will focus on the southern and northern areas of the field. Early during the appraisal stage, the data suggested the existence of an areal gradient in composition across the reservoir. As such, a clear understanding of this areal distribution in addition to the usual reservoir gas composition, properties and behavior was essential in optimizing field production and maximizing value. Over the course of field development, reservoir fluids from different well locations were sampled and analyzed. Various issues were encountered during this process including H2S stripping in down hole samples, contamination from stimulation fluids and quality assurance and quality control concerns in lab measurements. Resolving these issues allowed a coherent understanding of the compositional variation in the Arab Formations. To properly model the compositional variation, an innovative methodology was implemented by the team to initialize the dynamic model. The methodology consisted of two major steps. Firstly, PVT data was analyzed and correlations between H2S and other components were developed. Secondly, through PETREL, compositional maps were created. Ultimately, each grid block was assigned a unique composition honoring the areal variation in composition across each reservoir zone. In addition, empirical correlations between fluid components and plant product streams were developed through material balance analysis. Using product models, these correlations were input into the dynamic model which allowed estimated plant products to be output directly from simulation runs. Simulation forecasts of estimated plant products were later verified by actual plant yields, giving confidence in the methodology implemented. Further, this method allowed a quick turnaround in production planning and optimization thereby reducing the reliance on a fully- fledged plant simulator for short term gains and quick wins.