The incorporation of the smart technologies in injection wells has not been widely considered before this work, hence the originality.The world's demand for oil product is increasing gradually and lack of new significant discoveries has made it imperative to look for secondary processes and better technology that will help increase oil production. One of the secondary recovery mechanism used all over the world is waterflooding. Waterflooding is used in nearly all the fields in the world, it is used after natural depletion, and it's used for pressure maintenance and volumetric sweep of the reservoir. Smart well technology is another technology that is assisting in increasing oil production, it's a non-convectional well with downhole instrumentation (sensors, valves and inflow control devices) installed on the production or injection tubing. This work presents a methodology where waterflooding is been controlled by smart injector well technology to help optimize or increase the net present value of the Field. The optimization procedure was done on three different case studies of commingled reservoir having different layer characteristics; it involves vertical smart injector well and production well penetrating fully through the commingled reservoir. A set-up optimization procedure was applied, were rate allocation method was used at each zone of the smart injector well. In this research, the right rate allocation to each zone that gives the maximum Oil recovery or highest Net Present Value gives the answer to the Waterflood Optimization setback. The smart injector well use in this research has Inflow control Valves which can automatically open and close in order to meet certain reservoir or production requirements. Installing Smart Completion on the injector well gives an opportunity to control all cases of early water breakthrough and reduce water recycling in some reservoir layers; which will ultimately lead to an increase of 2% -8% in the Net Present Value and 6% -9% Cumulative Production of from the field. This Technology is highly recommended for Niger Delta fields to improve recovery and delay water breakthrough.

Latin Hypercube Sampling (LHS), unlike other simulation methods such as Monte Carlo Simulation (MCS), has not enjoyed wide applications in determination of reserve despite its capability to realize same accuracy as with the latter even with much fewer simulation trials. The parameters used in these distributions are extracted using software "digitizer" from different plot of values derived from measurements of reservoir and fluid properties. This work dwells on analysis of two depleted gas fields for which the ultimate recovery is known. The distribution of porosity, water saturation, reservoir thickness and reserve size are input to crystalbal software to generate cumulative distribution function (CDF) and Probability density function (PDF) of original gas in place (OGIP) for each of the fields. The accuracy of Latin Hypercube Sampling is analysed by comparing the actual ultimate recovery and the OGIP predicted by LHS. The calculated recovery factors of 68.7% and 93.3%, for water driven and depletion driven gas reservoirs respectively, compare favourably with those of known gas reservoirs. Therefore, LHS is a good estimator of gas reserve. It is recommended that similar study should be carried out on condensate and oil reservoir, particularly on Niger Delta fields. Introduction The determination of oil and gas reserves involves the preparation of estimates that have an inherent degree of associated uncertainty. Classifications of proved, probable and possible reserves have been established to reflect the level of these uncertainties and to provide an indication of the probability of recovery. The estimation and classification of reserves requires the application of professional judgment combined with geological and engineering knowledge to assess whether or not specific reserves categorization criteria have been satisfied. Knowledge of concepts including uncertainty and risk, probability and statistics, and deterministic and probabilistic estimation methods is required to properly use and apply reserves definitions. Reserves estimates may be prepared using either deterministic or probabilistic methods (Petroleum Society of CIM definitions-guidelines, 2002.).The deterministic approach, which is the one most commonly employed worldwide, involves the selection of a single value for each parameter in the reserves calculation. The discrete value for each parameter is selected based on the estimator's determination of the value that is most appropriate for the corresponding reserves category.