Gas reservoir development at inception is often linked to detailed surface infrastructure development and long term contractual agreements with only a few appraisal wells. A thorough and detailed technical estimation of the size of the pie is an important step in the right direction. This is characterized by seismic acquisition and interpretation, scanty appraisal wells proving useful reservoir and fluids properties data and contact tagging. Calibration of regional properties with nearfield analogue can also be quite useful. All these form the basis of the field/Reservoir development plan. For a gas development, the optimum development wells depend on a variety of factors identified at the field development stage often targeting the most viable crestal part of the reservoir for optimal development. Post drilling of development wells where reservoir static properties are fairly known and at the early stage of production when there is paucity of production data, it is imperative to adopt a robust approach to evaluate the technical UR. In early producing life of the reservoir when reservoir pressure data is needed perhaps the most, long shuttin-in to take static pressures can be abit problematic due to commercial commitments. There is heavy reliance on planned and unplanned shutins to take useful pressure data used in calibrating reservoir models. This paper takes a critical look at multiple approaches to estimating robust ultimate recoverable gas volumes with reservoir geology as an essential guide using tow distinc approaches; Detailed 3D simulation model and P/Z estimate method using Piper, McCain and Corredor z factor estimates. Lastly the range of uncertainties of the input data was used to estimate the low base and high cases.

Flowing Material Balance (FMB) and Rate Transient Analysis (RTA) have evolved as well and reservoir performance evaluation techniques which make use of the large amount of pressure data from permanent downhole gauge (PDHG). Meaningful analysis requires the pressure and production data to be continuous but often there are operational breaks in the data making analysis quite difficult. Case histories of FMB and RTA that use augmented non-continuous pressure data from PDHG as basis for modelling well and reservoir performance to deal with this gap are presented in this paper. The proposed method involves derivation of continuous pressure trend by splicing and merging depth-converted tubing head pressure data with non-continuous PDHG pressure data in the intervals where the later are discontinuous with appropriate quality checking to ensure no hump or sink at the transitions as well as consistency in trend. Any remaining gaps are then handled by interpolation of offset points. The augmented non-continuous PDHG data is then applied in FMB and RTA to estimate connected GIIP and remaining recoverable resources following an acceptable analytical or numerical history matching. A workflow to enable application of the process is documented in this paper. Results from the case histories are comparable with previously published 3D static and dynamic models. The results could be influenced by the noise level in the data but this could be managed with appropriate de-noising method like wavelength filtration which was used in this case study. This approach offers the maximum use of PDHG pressure data in reservoir surveillance not just as a real time monitoring technique but additionally as enabler in predicting life cycle performance of a reservoir in the absence of, or complimentary to 3D dynamic simulation model or other methods in the industry. It is simpler and less resource consuming performance-based approach than 3D dynamic simulation.

Understanding the dynamics of a reservoir based on performance and acquired data is key to optimal field development. This is the case for a matured gas reservoir with more than 2Tscf of gas in-place in the Niger Delta. Based on initial data acquisition during the field development planning, the reservoir was interpreted to be compartmentalized by series of intra-reservoir shales. After four years production, acquired performance data analysis suggests increased communication between reservoir units and lower range of in-place volumes. This is believed to be driven by high mobility of gas and presence of intra reservoir faults that breached the intra-reservoir shales. This updated understanding forms the basis of the re-evaluation of the reservoir. The depth uncertainty used to generate the low and high case top reservoir structure was revised from 60ft to 33ft (based on residual analysis). The dynamic model was re-calibrated with the updated static model using the Experimental Design (ED) workflow. Performance data from the producing wells were used to calibrate the simulation model to ensure consistent ultimate recoveries estimation. The estimated developed ultimate recovery from the reservoir simulation is comparable with the results from a P/Z analysis and material balance model. The novelty of this approach is the ability to manage subsurface uncertainty through effective use of well and reservoir data to improve reservoir understanding. Overall, the subsurface uncertainty management strategy ensured collaboration within the sub-surface team, effective use of the installed permanent downhole gauges, and integration of surface and sub-surface data in the update of the simulation model.

Acquisition of bottom hole pressure is a statutory requirement in Nigeria. In addition, pressure data provide a better understanding of reservoir responses to production for effective wells, reservoirs and facilities management. The data is used to calibrate dynamic and well models in order to improve the quality and reliability of predictions that feed into Annual Review of Petroleum Resources (ARPR) cycle. Despite its importance in the oil and gas industry, there are often delays in mobilizing for Bottom Hole Pressure Data acquisition due to deferment concerns, budget constraints and security challenges. This was the case with some gas wells in Aowa field in the Niger Delta region of Nigeria where the bottom hole data could not be acquired on scheduled to support the technical evaluation of resources within the given timeframe of the annual volumes reporting cycle. This paper is a case study on the determination of closed in bottom hole pressure (CIBHP) from Closed in Tubing Head pressure (CITHP) during well shut in periods using the Cullender & Smith methodology. The proposed approach involves derivation of bottom hole pressure data from measured closed in tubing head pressure and known gas gradient. The scope of implementation covered three gas wells in the Aowa field (AOWA 3, 4 & 5) that supply gas to NLNG and processed through a Central Processing Facility (CPF). The three gas wells are produced from three different reservoirs in the field with total expected gas rate of about 350 MMscf/d. These wells are significant to achieving the export nomination expected from the CPF. These wells came onstream in July 2013 and have produced as expected. The novelty of this approach is the elimination of HSSE risks associated with undue staff exposure in the field, obtaining fit for purpose quality data without production deferment and costing down OPEX as ca. US$22,500 per well can be saved due to non-contractor engagement. The work flow established by this method can be applied across other operating units for gas wells having similar operation challenges. The results obtained from this methodology compared favorably with actual measurement carried out later in the wells with the highest deviation of < 5%. The study revealed that the accuracy of the result using this approach is highly dependent on gas gradient.