Seismic Reservoir Quality Prediction, Khazzan Field, Oman

Abstract

Abstract We present a seismic analysis workflow to evaluate tight gas sandstone reservoirs from a case study of the Khazzan field Barik formation, which is currently under development. The work from this field is particularly important because seismic attributes are playing a critical role in optimization of the field plan, mainly by distinguishing areas of good productivity from poor productivity. Our evaluation starts with conditioning the migrated seismic data for AVO (Amplitude Variation with Offset) by reducing noise, flattening gathers, balancing amplitude and spectral frequency, and creating intercept, gradient and angle stacks. At the same time, a seismic rock property study is conducted, integrating acoustic well logs, petrophysical analyses and core data to model possible outcomes, and design the offset porosity and lithology volumes from conditioned data. Then numerous attribute maps are extracted from offset and stack data, including Extended Elastic Impedance maps from offset data and amplitude maps of various types from stacked data. Key attribute maps from stacked data include average amplitude from colored inversion and spectral decomposition over the reservoir time window. After these products are created, statistical comparisons are made between attribute extractions at well locations and porosity-height from petrophysical analyses of logs and core studies. Graphs, statistics and bubble maps of actual and predicted porosity-height are analyzed together to develop preferred predictions showing distribution of uncertainty over the area of interest. As development of the field progresses, seismic predictions of reservoir quality evolve with new wells being drilled, seismic data being improved and seismic attributes being tested. Initial efforts have already led to the optimization of the drilling schedule by re-scheduling wells from poorer to better areas, and planning for pilot wells to test areas of uncertainty. This seismic analysis workflow aligns with our goal to determine the degree to which seismic can be used to predict reservoir quality and guide field development, when integrated with geology, petrophysics and production data.