The study covers a giant oil field situated in Iraq. M formation is the major producing reservoir in the field, and is characterized by a complex heterogeneous carbonate system. Reservoir rock typing in carbonates is a critical process by which geological lithofacies are characterized by their dynamic behavior, which is needed for better reservoir characterization required for reservoir modelling and numerical simulation to optimize development plans and maximize oil recovery. The operator company has conducted a comprehensive reservoir characterization study for M reservoir involving, routine core analysis, SCAL, Static and Dynamic rock typing studies in M formation, alongwith routine geological and petrophysical analysis. Thomeer methodology was used for Static Rock Typing analysis, utilizing the extensive available Mercury Injection Capillary Pressure Data (MICP) to capture the complexity of the M carbonate reservoir, and the Thomeer parameters (G – shape factor, Bv – Bulk Volume and Pd – entry pressure) were derived for every pore mode of these selected MICP plugs. Five pore geometry groups were proposed based on modes identified in the PTR frequency distribution, then created five equivalent Static ‘rock-types’. These were given further reservoir context through integration with Petrography, Sedimentology and NMR data available from core and logs. Due to the complex nature of heterogeneous carbonate formation of M, the five major static rock types were further characterized by their dynamic behavior to reflect the interaction between the rock lithofacies and reservoir fluids. While porosity, permeability and pore size distribution characterize the rock texture, SCAL parameters, capillary pressure, relative permeability and wettability will capture rock-fluid interaction and will impact oil recovery from such complex heterogeneous system. Different methods were tried to correlate dynamic rock types in M formation including Classical rock typing methods based on logarithmic regression of permeability versus porosity cross plots, as well as Flow Zone Index (FZI) and Reservoir Quality Index (RQI) methods. This was followed by applying Winland method for dynamic rock typing characterization. This paper describes the successful workflow adopted in the study to define the Dynamic rock types for M formation based on Winland methodology, where a total of 16 core plug samples were selected using CT scans screening (2 plug samples selected from each of the major rock types RT) for Reservoir Conditions relative permeability testing as well as 4 samples were earmarked for ambient condition relative permeability measurements and further 4 plug samples were selected for wettability and capillary pressure testing covering all the major types. The Winland R35 methodology [1] was applied on the selected samples in order to verify if any of the core samples shifted from the previously defined static rock types. The new porosity and permeability and SCAL relative permeability and capillary pressure measurements for the selected samples were used as part of the workflow to calculate Winland R35 algorithm, then plotted to derive and characterize the new dynamic rock types for M formation in the field

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper summarizes the findings of a compositional simulation study of a gas injection pilot in a transition zone reservoir onshore Abu Dhabi. The field covers an area of more than 600 sq. km straddling land, islands, shallow and deep marine environments. A multi-disciplinary team including reservoir, petroleum, planning, conceptual design engineers and geoscientists, geologists, geophysicists and petrophysicists, was formed to examine different development options for the field. The team is faced with a number of technical and economic challenges to design an optimum field development scheme, maximizing ultimate oil recovery and minimizing development cost while maintaining high level of environmental protection through the whole life cycle of the field.

The tight F and D units of the Bu Hasa field, in onshore Abu Dhabi, have undergone limited production, and are considered good candidates for a miscible gas injection project.A field pilot was implemented with the objective of evaluating the potential of miscible gas displacement as a secondary recovery mechanism in this tight carbonate formation. A compositional simulation model was built to describe the mechanism involved in the process, and to predict the pilot performance.The Peng-Robinson equation of state was used with a 4 pseudo-components system, based on a 13 components formulation. It was tuned on PVT laboratory data, and produced a good match of experimental results of slim tube tests. A 3D radial model was constructed to represent the pilot. Simulation results indicate the development and propagation of a miscible front.After validation by field data, the model will be used to predict the performance of a miscible gas injection development scheme, extended to the whole reservoir.

Objective/ Scope Production logging analysis is essential to understand and evaluate reservoir performance throughout the lifetime of an oil well. Data acquisition and analysis is known to be challenging in modern extended reach horizontal wells due to multiple factors such as conveyance difficulties, fluid segregation, debris, or open hole washouts. Advanced compact multiple array production logging tool (APLT) is proposed to minimize the uncertainties related to these challenges. Method, Procedure, and Process The proposed sensor deployment method provides a comprehensive borehole coverage, thus maximizing the amount of subsurface information collected to evaluate the production performance of a horizontal well. Essential measurements are combined on six individual arms. Each arm is independently deployed which guarantees the best borehole coverage in a variety of borehole condition. Robust mechanical arm design minimizes damage, allows tolerance to decentralization, and provides greater confidence in determining the sensor locations. Each arm utilizes two fluid holdup sensors (Resistance, Optical) and one velocity sensor (Micro-Spinner). Co-location of the sensors minimizes the uncertainty related to sensor spacing when compared with previous generation of APLT. Results, Observations, Conclusions The new sensor deployment method and analysis results are discussed showing the added value in barefoot completion as well as advanced ICD completion. The holdup sensors response from previous generation APLT is compared to the advanced tool and how it relates to better borehole coverage. The results also illustrate use of high frequency optical probes for phase holdup determination. In addition, the optical probes are used to confirm bubble point pressure at in situ conditions by confidently detecting the first gas indication in the tubular. The results clearly show how a compact APLT maximizes the borehole coverage in highly deviated and horizontal wells. This is critical in collecting representative data of all segregated fluids which enables more accurate interpretation of the flow profile in the well and better understanding of reservoir performance. Novel / Additive Information The novelty of the new instrument is the ability to maximize the amount of subsurface production logging information collected with low uncertainty and minimum operational risk.

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