Permeability is one of the most important parameters of reservoir rocks; it defines the capacity of rocks to transmit fluids in pore spaces. Permeability prediction is of extreme importance in deciding the field development strategy for green reservoirs. The reservoir rocks are made up of grains, cement and pore network. The pore network is made up of larger spaces, referred to as pores, which are connected by small spaces referred to as throats. The pore spaces control the amount of porosity, while the pore throats control the movement of fluids and the quantity of rock permeability. Generally, the sources of permeability measurements in green field are from core data, well test data and Nuclear Magnetic Resonance (NMR) data. However, core information, well test information and NMR information are usually very limited due to high cost of acquisition making justification usually difficult. The consequence is that we have very low ratio of cored to the total reservoirs in the Niger Delta. This paper discusses a methodology for accurately estimating permeability using analogue fields/reservoirs core data in green reservoirs. The main factors to consider in choosing a suitable analogue includes Facies classification, relative depth of the reservoirs, average porosity and histogram of the Gamma ray values between the subject and analogue reservoirs. This selection is usually an integrated effort between the teams Geologist and Petrophysicist. In this study, two fields were selected where permeability prediction was based on analogue core data. A robust Niger delta wide analogue selection process was applied first to identify the analogue field where core data exists. After selection of the analogue field, facies-wise poroperm transform was built. This poroperm transforms were then validated in one of the fields where real core measurements were available post study. This blind test with real core permeability data indicated an excellent match with analogue based permeability model. In the other field, the analogue based permeability was validated against NMR and mobility data acquired in some of the reservoirs. This workflow establishes the robustness of using existing analogue data to reduce the subsurface uncertainty and justify an integrated workflow of estimating permeability in the green field rather than acquiring a new data to support development decision.

One of the major challenges in field development is to estimate the possible oil-rim thickness, when only known contact is Gas-Down-To (GDT) or Oil-Down-To (ODT), and where seismic analysis cannot resolve the uncertainty. A reliable, repeatable, and practical technique to estimate the ranges of possible oil-rim thickness with the regional analogue would allow for making development decisions, as well as meeting the local regulatory requirements. An analog database with numerous proven hydrocarbon (gas and oil) column heights provides a trend for "gas-to-oil column ratio" by depth, which can be used for predicting possible oil-rim thickness at specific reservoirs with the contact uncertainty. For all the analog reservoirs, fluid thicknesses have been tabulated and a "gas-to-oil column ratio" has been calculated. A simple plot between the "gas- to-oil column ratio" and reservoir depth reveals a certain trend of increasing "gas- to-oil column ratio" by depth. In addition, database also provides a cumulative distribution of regional column heights, which could be used to constrain the maximum estimated hydrocarbon column thicknesses. The trend of increasing "gas-to-oil column ratio" by depth indicates that gas-columns gets much bigger compare to oil-columns as the reservoir depth increasing. With given depth information and estimated "gas-to-oil column ratio" from the database, it is possible to estimate possible range of oil-rim thickness. By investigating the scatter in the trend, it is also possible to estimate a range of "gas- to-oil column ratios". With the help of this methodology, in absence of any definite fluid contact, it is possible to estimate a range of oil-rim thicknesses, which has an impact on field development scenarios; i.e. "gas-only", "oil-then-gas", or "concurrent oil-and-gas" development options. In addition, it could also help field development plan to meet the regulatory requirements; i.e. providing a strong case not to develop or appraise the oil rim.

Estimation of initial Hydrocarbon-Water-Contact in the light of conflicting information is critical to overall field development plan and project economics. Understanding the causes of conflicting information requires an integrated investigation of potential sources of the information and a structured approach for developing and ranking plausible explanations. R11 reservoir in Yama field has conflicting information from two wells drilled 19 years apart, which indicates the possibility of compartmentalization within the reservoir or pressure depletion from a nearby field. The discovery well, which is closer to the crest, encountered a GDT and GWC is estimated to be at 9790 ftss with an assumed regional water gradient. A later appraisal well, located at the flank of the structure, clearly logged a GWC, but it is 126 ft. deeper than the estimated GWC from the discovery well. In addition, the appraisal well recorded 120 psi lower pressure than the discovery well. This conflicting information could be explained by 4 possible scenarios: 1) Errors in measurements, 2) Uncertainty in regional water gradient line 3) Reservoir compartmentalization 4) Pressure depletion from a nearby producing field. While the vintage of tool for pressure and depth measurement in the discovery well is relatively old, the difference of 126 ft. due to measurement error is unlikely. All the pressure points align quite well and estimated depth measurements errors are much smaller. On the other hand, pressure analyses with a range uncertainty in regional water gradient could narrow the difference, but not all of it alone. Possibility of reservoir compartmentalization due to faulting has quite a large impact in overall field recovery and the reservoir development. The last possible explanation for the conflicting information is the potential depletion of the pressure from a nearby field via a connecting aquifer. Analyses indicate that while it is possible to lower the reservoir pressure due to production from a nearby field, the magnitude of the pressure-drop would have been significantly smaller. Based on a series of static and dynamic modelling as well as sensitivity runs, the conflicting information can be explained by pressure depletion and the reservoir is in communication. This scenario is selected as the "Base Case" for development planning. On the other hand, the compartmentalized scenario is also considered a possibility but as a "Low Case" scenario, hence it is included in field development scenarios and the impact of it is built in the project economics.

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.