Geobody Interpretation and Its Application for Field Development

Abstract

Geobody identification via Spectral Decomposition has been used to optimize the development of a reservoir for a green field (Nime – not a real name) in the shallow offshore Niger Delta. The target reservoir (NM1 – not real name) is covered by a 3D seismic data that was acquired and processed using Post Stack Time Migration technique in the late nineties. Six exploration and appraisal wells have been drilled through the reservoir to date. Stratigraphically, the reservoir is approximately a 250- feet thick high net-to-gross (0.98 – 1), high porosity (0.26 – 0.28) sandstone interpreted to be stacked channel and shoreface sediments that were deposited in marginal marine environment. Given the high net-to-gross and porosity of the reservoir and absence of any intra-reservoir fault that may compartmentalize the reservoir, the reservoir is deemed laterally continuous and connected. However, fluid contact values derived from reliable combination of gamma ray, resistivity, neutron and density logs from the wells indicate a difference of 25 feet for the oil water contact (OWC) in the reservoir. To fully understand the contrasting information viz 25ft OWC difference in a highly sandy and ‘connected’ reservoir, spectral decomposition volume attribute was generated from the 3D seismic data and analyzed to determine the reservoir architecture. The spectral decomposition workflow applied involved two basic steps: i) Spectral analyser – to determine dominant frequencies in the 3D seismic volume; and ii) Spectral decomposition – creating 3D volumes for the dominant frequencies and analyzing them with the aim of identifying geobodies (channels) and defining the reservoir architecture. Prior to carrying out the Spectral Analyser, the 3D seismic cube should be ‘cropped’ to the required area of interest (AOI) to reduce computer memory required to run the algorithm. It is also advised to run any post-processing seismic workflow (e.g. VanGogh) that will increase signal to noise ratio before spectral decomposition. This paper presents the details of the Spectral Decomposition workflow which can be applied for identification of geobodies and how its result was used to optimally plan development wells in the target reservoir to mitigate an unlikely compartmentalization of the reservoir.