It is commonly practice in reservoir modelling to use constant kv/kh values to define vertical permeability in numerical reservoir models. This is often in response to paucity of core data and need to reduce simulation run time. That traditional approach works fine in fairly homogeneous reservoirs; however, in reservoirs with heterogeneity, due to more complex depositional environment like shallow marine deposits, it is not necessarily a good practice to assume single averaged kv/kh values to represent vertical connectivity for such reservoirs. This paper highlights the importance of understanding reservoirs' vertical connectivity by properly defining kv/kh as a function of lithofacies and evaluating its impact on history match and prediction outcomes on one case study for a heterogeneous brown field reservoir with complex depositional environment in the Niger Delta. Core data, wellsite cuttings data along with available production, and pressure data were used to calibrate the petrophysical and numerical dynamic models. The study also considers substantially a multi-disciplinary approach to uncertainty management, using Experimental Design (ED) methods to understand and validate kv/kh ranges as a function of lithofacies. This methodology was successfully implemented across several oil reservoirs (D2000-D7000 EXHJK) in a recently concluded field project in the Niger delta of Nigeria. As an example, this paper discusses the results, and recommendations for one reservoir (D5000X) selected out of this project study. The main objective from this project is the importance of understanding vertical connectivity in a complex reservoir by capturing heterogeneity and major geological features in the integrated 3D dynamic model aiming to achieve acceptable history match at reservoir level, but also more importantly on a well-by-well basis. The robustness of the integrated dynamic model provided higher level of confidence for prediction, and resulted with increased certainty for the forecasts by a factor of 3 (reduced solution space) after implementing variable kv/kh as function of facies.

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Analytical studies serve as the primary (first pass) models for evaluating field performance before proceeding to full field numerical models. The decision to proceed to a full field numerical model is usually determined by results of the analytical study and cost of the study relative to the estimated reserves in the field. This implies that for smaller fields, analytical studies may be the major reference for field development. This paper presents the workflow and results of integrated analytical studies performed on Kukaku, an onshore field in Niger Delta belonging to the Nigerian Petroleum Development Company (NPDC), jointly operated by NPDC and SIPEC. The studies done include petrophysical analysis, welltest (DST) interpretation, NODAL™ analysis, choke performance studies, coning studies and material balance forecast. The paper focuses on key areas of integration in the workflow and best practices in the study. Conclusion from the study is that integration is also a key concept in analytical field studies especially for smaller fields in which the reserves size precludes the use of expensive numerical models. In such cases, critical analysis of available data and best use of such data to generate rigorous and robust analytical models are key to the optimal development of such fields.

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3D reservoir modelling of stacked reservoirs is often difficult, due to interplay of various uncertainties related to heterogeneity of the sand units modelled together within the stack. In the past, reservoir simulation had been used to model stacked reservoirs for commingled wells with varying predictive capacity. Typically, dynamic models use conventional approach in assessing uncertainties, involving discrete sensitivity of uncertain parameters and often lack robust subsurface uncertainty management. Additionally, handling dynamic cross flow issues by modelling of control valves in such cases presents production allocation challenges. Huge man-hours are needed for several run times, without achieving relatively good history-match and predictive capacity. As a result, only base-case history-matched model is developed; thus robust assessment of impact of sub-surface uncertainties on the predictions is usually inadequate.This paper details a multidisciplinary approach adopted in integrated dynamic modelling of stacked reservoirs in a Niger Delta field using experimental design methodology. The phased development was aimed at full-scale reservoir development of multi-zone and commingled wells. Instead of single average for each sand unit, facies-dependent kvkh values were required to adequately capture reservoir heterogeneity for the complex depositional environment. Field-wide history-matches for 23 reservoir blocks and over 70 individual conduit matches were done to calibrate the simulation models. Model robustness was conducted through blind-testing and calibration with carbon-oxygen and openhole log data from newly drilled wells.From the model predictions, recoveries for existing conduits from simulation models were benchmarked against Decline Curve Analyses and the results compared closely. Response Surface Models were used in selecting best history-matched realizations. 1P, 2P and 3P models were selected from the ultimate recovery probability distribution curves of these history-matched realizations. The modelling of interval control valves settings within the stacked models and use of smart well routines assisted evaluation of recoveries from planned commingled wells.