Reservoir Study of the Largest Oil Field in Argentina - A Two Reservoir 2200 Well Simulation Model

Abstract

This paper describes the processes incorporated during the simulation study of the Chihuido de la Sierra Negra Field in Argentina, which is presently the largest oil field in the country. The field was discovered in 1968, and an aggressive water injection program was started in 1995. So far the oil production from this field is 65 million cubic meters and the water injection is 158 million cubic meters. The field has two separate stacked reservoirs that are structurally complex with different fault systems and fluids. Both reservoirs are highly compartmentalized with each compartment having different water-oil contact. The upper reservoir is composed of 6 isolated geologic layers, with each being different depositional environments (sand bars, dunes, fluvial channels, etc.). The presence of unconformities and volcanic intrusions further complicate the reservoir communication and plays an important role in flow behavior. Currently, the field has 734 production wells with commingled production from both reservoirs and the isolated zones with in the upper reservoir. Approximately 1250 injection strings are currently injecting water. The purpose of this study was to provide a detailed reservoir characterization to optimize recovery and to create a simulation model with predictive capability that can be used in improving field management. To achieve this purpose a 900,000 cell simulation model was constructed. This paper will discuss some of the challenges encountered during the history matching of the field model. The identification of the compartment boundaries and their associated water oil contacts (57 contacts) required the development of a new consistent approach. This method provided significant accuracy and time savings over the traditional approach of iterating between history matching and reservoir characterization. The overwhelming volume of data and the volume of simulation results for 2200 well strings required special considerations for pre- and post-processing. New tools were needed to quickly modify the simulation arrays and review all the wells in an efficient and timely manner. As the history matching progressed many additional practical tools were developed. This paper will discuss the significance of these innovations and tools to achieve a successful history match in a timely manner. Introduction Chihuido de la Sierra Negra is the largest oil field in Argentina. It is located in the Neuquén Basin at 200 km Northwest of Neuquén City (Fig. 1) This field has three main clean sand reservoirs within the Lower Cretaceous Huitrin formation1. These are the Troncoso Inferior, the Agrio Superior and the Avile members. The measured depth where the producing intervals are located varies from 1100 to 1300 meters. The whole productive oil column is divided into ten (10) geological layers extended in a gross thickness of 200 meters. Fig. 2 shows the geological members and the layers present in this field. The shallower reservoirs (~1100 meters measured depth) Troncoso Inferior and Agrio Superior account for 60% of the ultimate recoverable reserves of the field. The depositional environments in the Troncoso Inferior Member include Aeolian dunes (5T and 4T intervals) and fluvial channels (3T and 2T). The middle portion of the productive column (Agrio Superior) is formed by marine sandbars (3A, 2A, 1A and 0A). The detailed reservoir characterization showed that an unconformity surface exists between the Troncoso Inferior and Agrio Superior members. During the simulation study the unconformity surface was verified to be a flow barrier between the two members. The deepest reservoir, Avile Member, is found at ~1300 meters (MD) and is composed of very productive Aeolian sand dunes. All the geological layers are isolated except 5T and 4T. Certain igneous sheets (volcanic intrusions) were correlated using the well logs that were available in the study area (Gamma Ray, Induction, Density and PEF). These identified intrusions have the potential of modifying the communication throughout the field. Fig. 3 shows an example well log with identified volcanic intrusions.

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