If a well loses it producing potential before depletion, then the pressure analysis of the well system should be carried out to ascertain the cause. Nodal analysis, is one of the analysis methods which is aimed at analysing pressure distributions across different nodes. This analysis will serve as a guide to revamping the well. This paper utilizes nodal analysis simulation approach to study the cause of pressure drop in a well system. Inflow performance relation (IPR) and vertical lift performance (VLP) were used to determine the pressure distribution in the well attainable at various flow rates and wellbore condition. Results show that nodal analysis method can be used to obtain prevailing well bottom hole pressures at various flow rate, the flow rates responsible for a unit pressure drop in a well system, the pressure loss across perforation and tubing using IPR and VLP of the well system respectively. Well completion strategies are adequately advisable from application of nodal analysis.

Considering that well test is an asset evaluation tool, condensate well testing is designed to address the uncertainties in retrograde performance with respect to various flow regimes under certain completion strategies and surface facility design. Condensate banking/trapping around the near wellbore due to liquid dropout (heavy end fraction condensation resulting to high reduction in effective gas permeability), the desire critical condensate saturation to re-establish mobility, the effect of interfacial tension and the capillary pressure present between the immiscible fluids can be observed and possibly addressed from well testing and analysis. A designed pressure scheme suitable to reduce productivity losses is adequately advisable from well test. Well test (which is a variation in sand phase pressure with time) can be used to determine: the dynamism in rock and fluid properties, underground withdrawals and cash flow. It could also serve as a factor for joint venture agreement and sale/purchase of assets. These achievements are based on excellent reservoir/well management initiated by accurate performance interpretation and forecast. The discussion of this paper is centered in the use of production testing and analysis for enhance condensate reservoir/well management. Various evaluation criteria's (Reservoir Deliverability, Well Productivity and Completion Strategies) were deployed in the characterization of the reservoir/well performance using simulated field data. However, back pressure, process facility design, surface data recordings and sample analysis under selected surface operating conditions were used to simulate the well stream process. This research has been able to shown that: production well testing and analysis can be used to determine the maximum attainable drawdown that will increase production and delay condensate liquid dropout around the wellbore. The similarities and variations in the results obtained from Maximum Efficiency Rate (MER) test and Bottom Hole Pressure (BHP) test as regards the aforementioned criteria's considering condensate behavior and the necessary maintenance (pressure, completion, wellhead etc) that will be required to sustain and/or improve production performance has been discussed.

A method of optimising gas production from condensate well in Oredo field by simulating surface proportional integral derivative controller, downhole transmitter, wellhead and bottomhole chokes is presented. This method overcomes the potential risk of high backpressure imposed on the production tubing by manual choking or other control solutions using wellhead valve. Firstly, a model of Oredo well O7 is constructed with a closed node constituting the reservoir unit and a surface pressure node on the wellhead. An automated pressure integral derivative controller that senses and controls the bottomhole flowing pressure by actuating the wellhead choke is then installed at the wellhead. Measurement input to the auto-controller is delivered via an insitu transmitter. This design approach is successfully applied to the well O7 model through a commercial multiphase simulator on well models and provides a condensate banking monitoring mechanisms with improved production output.

An enhanced neuro-fuzzy technique is deployed in production optimisation and fluid flow analysis for wells drilled and completed in Oredo oilfields Niger delta Nigeria. The impact of historical production data, reservoir rock and fluid properties, well geometry, architecture, completion profile and surface data on overall well deliverability is incorporated in the model. The artificial intelligence training process is complete at the point a minimum quantifiable error is obtained or when a value less than the set tolerance limit is reached. Production data obtained from the short and long-strings for wells completed in Oredo field was processed, analysed and input into the enhanced neuro-fuzzy algorithm. The adopted enhanced neuro-fuzzy system is capable of modelling the direct approach of Mamdani and that of Sugeno in a five-layer feed-forward neural network and fuzzy logic process designed and implemented in a C/C++ numerical computation objected oriented platform. This study highlights the significance of data analytics and artificial intelligence in well performance prediction and cost reduction and optimisation in oil producing wells.

A new pseudo-radial pressure model for inflow performance analysis and near-wellbore condensate banking deliverability is developed. Analysis of condensate banking and evolution in near wellbore region (i.e. zone 3) has been extensively studied. The new zone 4 region identified in this work will help in delineating the limit of retrograde condensation and the onset of revapourisation. Revapourisation after retrograde condensation is usually not accounted for in most field applications. However, in mature fields such as the Oredo field investigated in this study, revapourisation and near wellbore dynamics play an important role in optimising production from the field. The results of the newly formulated model captured the transient retrograde revapourisation near the wellbore for the well X studied in this work.