The field, a Late Ordovician gas condensate reservoir located in the Illizi Basin of the Algerian Sahara Desert, was put on production 6 years ago. It is the off-centred gas cap of a greater oil reservoir whose production was initiated by Sonatrach in 1967. The reservoir is characterised by its extreme geological complexity. The Late Ordovician (Unit IV) corresponds to a glacial period in the Saharian Basins. The heterogeneity of the reservoir -especially the strong variations in thickness -is such that it is extremely difficult to predict the performance of new wells, even when located in a well developed area. The presence of fractures organised in corridors increases even further the reservoir complexity. This paper presents the ways in which those challenges have been tackled in order to obtain both a reliable geological and dynamic model. It is shown how this characterisation was made possible by the integration of all the available information: seismic, geological and dynamic data.The matrix modelling was performed though the definition of electrofacies. Outcrop observations, depositional models as well as seismic data were used to define the internal layering of the geological model.The fracture model was achieved by integrating the curvature of the top reservoir horizon. It was confirmed and refined through comparison with borehole imagery (BHI) logs and dynamic data (mainly well tests and historical production data). Fracture conductivity was adjusted such that well productivity was respected. The outcome was a Discrete Fracture Network (DFN) model that was then upscaled and integrated into a single medium dynamic model.The final outcome is a dynamic model in which the history matched process was greatly improved. The predictability of the model was tested in an under-developed area of the field where new wells have recently been drilled. A fairly good agreement between the model and the reality was found in areas already appraised. In completely undeveloped area, the model was less successful.
Rospo Mare is a heavy oil fractured karstic carbonate reservoir producing since the 80's. Reservoir pressure is constant due to a strong aquifer tilted toward north east. The producing wells are systematically operated at critical rate to prevent water production (no water treatment installation). The paper is focused on the modeling of the fractures and the karst system in conjunction with an innovative history match approach used to match the forced anhydrous oil production and to represent the complex water position and behavior through time.
As the main fracturing phase of Rospo Mare reservoir occurred before the karstification phase, the dissolution of the carbonates was guided by the existing fracture network. The karst system and the fracture network were modeled together thanks to a fracture model that includes several enlarged fracture sets and lineaments. The fracture modeling was also guided by the relative compactness of the matrix facies distribution. Because of limited data for fracture characterization, the dynamic characteristics of fractures, particularly the aperture of enlarged fractures, were fully considered as history match parameters. The history match approach consisted in using both the historical oil production and the prediction period to make sure that the wells were producing at their critical rate and ensure a realistic displacement of water at both field and well levels. This unusual strategy was necessary because of lack of data to constrain history match (no water and gas production, no pressure variation).
Therefore the history match was performed by taking into account the prediction period through a do nothing case scenario. Based on the assumption of critical rate, a decline of the oil production rate is expected during the prediction period. This allowed assessing the vicinity of water at wells: both the rise of the water table and the coning effect at wells. The matched model successfully honors the water displacement and position at key wells including the last two side tracks drilled in 2012. The model allows a good representation of the reservoir physical behavior and provides a useful tool for piloting the field and assisting future decisions.
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