Reservoir quality in terms of Net-to-Gross (NTG) remains one of the critical components in determining the Hydrocarbon-initially-In-Place (HCIIP), recoverable reserves and production rates of any producing field. Often times, fluvial channel and shoreface deposits are credited to have very good reservoir qualities, hence are choice candidates for completions post-drill of the well. In addition, examples exist of heterolithic sands from which considerable reserves have been recovered during the life-cycle production of the Cream Field in the Niger Delta basin, Nigeria. Improved production from these reservoirs is associated with optimization of well designs. Heterolithic deposits are made up of interbedded sand and mud/shale. These deposits are typically laid down in environments like the tide dominated deltaic and estuarine environments as found in the Niger Delta of Nigeria.The Heterolithic sands found in the field to be discussed are mainly lower shoreface sands with lesser transgressive sand units; lower energy, variably sorted sandstones which are typically finely laminated and commonly intensely bioturbated. There is a continuous transition between heterolithic and shoreface sands. Reservoir quality tends to increase upwards as the heterolithic sands grade into shoreface sands.The sands have poor Kv/Kh values due to presence of shale laminates within the sand deposits. This exacerbates the poor sweep efficiency of the oil with high possibility of by-passed oil. The overall impact of these challenges is low recovery factors assigned to the sands.Due to the properties and nature of the heterolithic sands mentioned above, there is usually low pressure support due to poor aquifer connectivity as a result of the depositional environment, thus triggering a depletion drive mechanism.Interestingly, some of these heterolithics hold considerable recoverable volume that makes the exploitation of such reserves important. Such is the case offshore Norway, Alaska, Canada, Venezuela, Russia, Nigeria and indeed world-wide. As a result, production optimization therefore becomes critical to maximize recovery from wells completed on this facie type.The paper reviews the occurrence of this heterolithics in a field in the Niger Delta, the challenges faced with the current completion strategy and the reservoir management practices. A major challenge as observed in conventional crestal completion on the structure is early gas breakthrough from secondary gas cap formation. Methods of enhancing recovery from heterolithics using improved completion strategy and the requisite reservoir management practices are set forth in the body of the paper.Completion strategies like horizontal wells targeted at the good quality sands has shown an additional potential 1300bopd (seen in the performance of the only horizontal well in the field) as compared to performance of conventional wells, simulation study of water injection and gaslift has also indicated an increase in reserves by 10MMstb.

Well performance evaluation and prediction via decline curve analysis (DCA) requires defined abandonment conditions (Abandonment BSW and oil rate) to estimate the developed ultimate recovery (DUR) of a drainage point. Abandonment BSW and oil rate are derived from well models which require abandonment reservoir pressure and Gas-oil-ratio (GOR) among others as inputs. Good understanding of the performance of a reservoir is necessary for the prediction of abandonment GOR, and this prediction requires a systematic approach. The assumed value of producing GOR has a direct impact on the magnitude of the hydrostatic and dynamic pressure loss in a production tubular and hence it is a very important parameter in the vertical lift performance of a well. Similarly, the the reservoir pressure at abandonment is an indication of the energy available from the reservoir for lift hydrocarbon fluid s from the bottom of the producing wells. This paper illustrates the methodology employed for the estimation of abandonment reservoir pressure, GOR and BSW in support of well performance evaluation and reservoir management. Case studies for saturated and undersaturated reservoirs with weak-to moderate aquifers are considered.

Accurate reservoir performance prediction m a structurally complex brown field is very important for generation of reliable production forecasts, location of possible by-passed oil estimation of reserves and optimal well/ reservoir management. Reserves estimation is one of tire key functions of Petroleum Engineers and it requires an integrated approach for tellable estimates to be made. The traditional techniques include Decline curve analysis, Material balance. Volumetric. Analogues and Numerical Reservoir simulation. Reservoir X is a structurally complex reservoir nr Field Y in the Niger Delta Basin. It came on stream in 1970 with 3 wells. Eight additional wells started production between 1972 and 1990. Five infill wells were drilled and completed between the years 2000-2005. However, due to operational and technical reasons (which are beyond the scope of this paper), 2 of these wells are yet to be put on production Over the years the reserves associated with these 2 wells have been estimated by analytical means (Volumetric and Material balance methods). However, there was the challenge of investigating the impact of fluid saturation changes around these wells, occasioned by the production fiom offset wells, on the reserves estimate obtained fiom material balance techniques These challenges necessitated the full field 3D integrated reservoir modeling The reservoir contains 9 blocks in which 8 are densely faulted. The material balance analysis, being, at most, a onedimensional model, was deficient in robustly assessing the subsurface uncertainties which includes fault sealing potential and fluid contacts movement. This paper discusses the techniques employed in building die static and dynamic models and shows a comparison of the reserves estimate results fiom analytical techniques versus 3D dynamic estimates.

Gas Cap Blowdown (GCBD) involves a process of depressurizing the gas cap of an oil reservoir to produce the associated gascap volumes, more often after the oil rim has been depleted of significant oil production. Thus, the optimal development plan for such reservoirs carries both large technical and commercial uncertainties and a robust technical evaluation is required to underpin commercial decision. In most moderate to strong aquifer drive reservoirs, the displacement of gas as the oil rim moves upwards into the gas cap causes residual oil losses with trapped gas. This paper details the integrated study of a gascap development of oilrim reservoir initially developed by twelve (12) oil wells and with over 40 years of production history; and overlained with an undeveloped huge gascap with M-factor, m>1.6. The reservoirs comprise of number of communicating blocks by a series of nonsealing synthetic faults and a number of nonsealing transverse faults of up to 200 ft throw. Full scale 3-D simulation models; using the Shell's proprietary 3D dynamic modelling application; Modular Reservoir Simulator (MoReS) were deployed to assess subsurface uncertainties and history match reservoir performance of the reservoirs. The impact of resaturation of original gas cap volume and timing of gascap blowdown on the ultimate recovery of the gascap were exhaustively evaluated. Optimal development of the gascap was assessed against a range of technical uncertainties which then formed the basis for development of other reservoirs in the field that were not subject to the full uncertainty assessment. From the results of the subsurface uncertainty analysis and extensive history match, three (3) gas wells targeting the gascap were proposed to develop the reservoir and optimum timing of gas cap development was evaluated, while concurrently producing the remaining oil volumes with exising wells. In addition, the results from sensitivity analysis evaluated different timing for commencement of gascap blow down and the associated incremental recoveries. Also, for residual oil in the presence of gas, reduced range of values upto 30% of the oil-to-water residual saturation results due to the different blow down timings.

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.