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Maximizing the application of horizon slice mapping

Proceedings Title : Proc. Indon. Petrol. Assoc., 28th Ann. Conv., 2001

Horizon slice mapping is an effective tool that the seismic interpreter can employ to enhance the understanding of reservoir architecture, thereby leading to more optimal positioning of development and exploration well locations with minimized geological risk. In contrast to time slices, which are created from the processed 3-D data volume at a constant time level, horizon slices are created using the interpretation of key regional or local seismic reflectors. Slices are created at, above or below the key horizon. Therefore, horizon slices remove structural elements from a display, provide an image of stratigraphic variations across an area and often provide new insights into the depositional environment and lateral distribution of geologic facies.This paper illustrates the new insights gained from horizons slices in the Offshore West Madura PSC, located 55 km north of Surabaya. In 1999, 1150 km2 of 3-D seismic were acquired over the block and processed. Currently, regional interpretations of key horizons are being refined. Within the shallower Pliocene and Pleistocene section, horizon slices delineate channel sand systems. Meandering channels and oxbow cut-offs are often clearly visible and mappable. Many of these features are gas charged. These shallow drilling hazards can be recognized and avoided by evaluating this interval with horizon slices.In this block the Early Miocene Kujung I Formation is the primary producing interval.This reservoir comprises reefal buildups. Horizon slices have offered new insights and have contributed to aiding our understanding of the growth of these carbonate build-ups and their internal architecture.Future activity will focus on deeper Kujung intervals and its underlying clastic “Pre-CD Formation, where more subtle stratigraphic traps may be found. Here too, the use of horizon slice mapping, in conjunction with a dynamic geologic model, can help unravel some of the secrets of sand distribution that would be difficult, if not impossible, using only 2-D data.

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