Integrated evaluation of wet gas reservoir : minimizing volumetricuncertainties using dynamic analysis

There is a growing research effort to understand the most reliable approach in estimations ofoil and gas reserves, through different procedures such as the volumetric, Material Balance,Reservoir Simulation, Decline Curve Analysis (Production performance analysis), whichdepends on the understanding of the physical flow characterization of the formation, productiondata, and recently dynamic nature of reserves. While most researchers were motivated by staticnature of dry gas reserves and hence, their reserve estimations consider parameters typical ofsuch reservoirs, formations where associated gas is found has continued to be a challengeparticularly in sandstone reservoirs.In this study a novel approach of adopting integrated experimental and analytical techniques,using digital core flooding system to establish dynamic properties of the reserves was used incombination with analytical techniques including Volumetric, Decline Curve Analysis,Reservoir simulation and Material balance.Experimental study was conducted in phase I to determine rock properties, such as effectiveporosity, permeability and distribution of pore size, generally regarded as petrophysicalproperties, the core characterization measurement of the dimensions and weight wereperformed using the Vernier calliper, weight measurement balance.In Phase II PVT (Pressure, Volume and Temperature) analysis for gas composition and fluidproperties were also carried for a wet gas field case study (Ogba Essale). A sub set of thesample was flashed from reservoir condition to atmospheric condition (758.31 mmhg and 82.4f). The products (i.e. gas and oil) were analysed by gas chromatographic technique and thenmathematically recombined to obtain the reservoir fluid composition. Constant compositionexpansion (CCE) test, Constant volume depletion (CVD) test were performed at the reservoirtemperature of 224.6 f. multi-stage separation test was performed at the specified surfaceprocessing condition, the results were subsequently inputted for reserve evaluation into variousmethodPhase III Involved Modelling and computer simulation Static geologic models in Petrel andReservoir simulation models in Eclipse 100 and 300 were built and utilized to estimate thehydrocarbon volumes. Similarly, in this phase Declining Curve Analysis using Oil FieldManger (OFM), Material Balance and Volumetric calculations was carried out.Phase IV focused on Single Phase flow of Buff Bera using Navier-Stokes equations andDarcy`s law to describe single-phase gas transport and free gas at the pore spaces. The modelswere developed using water salinity representation of the wet gas field in the case study, tosimulate the performance of the natural gas reservoir in assessing the performance ofproduction from natural gas reservoir.Phase V: Core flooding for two-phase liquid movements under unsteady state or steady statecircumstances and single-phase gas steady-state experiments, was conducted.Phase VI involved the application of COMSOL-Physics, constitute the creation of a pore-scalefinite element mesh of sandstone core samples from SEM images and based on the numericalsimulation of sandstone at a pore-scale level based on experimental resultsiiiPhase 7: Results analysis and discussions: The findings indicated from the characterization(phase I) indicated for porosities of the respective core samples: Buff bera 24.55% and 20-22%,Castle gate 29.31% and 27-29%, Boise 30.35% and 28%, Bandera Grey 19.67 and 19-21%,and Grey Beira 20.18% and 18-21% for experimental and factory values respectively. Whilepermeabilities values indicated Buff Beira 458.1mD and 350-600mD, Castle gate 1434.8mDand 1300-1500mD, and Boise 2196.4mD and 2000-4000mD for experimental and factoryvalues respectively, the porosity and permeability values by the experiment deviated slightlyfrom the factory porosity values. The experimental result showed good agreement with theliterature data under dynamic conditions, subsequent data of the Buff Berea experiment resultwas implemented into COMSOL multi physics software to characterize gas transport of singlephase flow at pore scale level. Also, for this study, the Buff Bera values of porosity andpermeability were imputed for all the reservoir evaluation technique except for Reservoirsimulation of which porosity was estimated from the bulk density and sonic logs using averagegrain density of 2.65g/cc, 1.00g/cc and 0.85g/cc for fluid density, 53msec/ft. for average grainvelocity and 189msec/ft. For pore fluid velocity, the net sand of the reservoirs was estimatedby applying Petro-physical cut-off (vsh=0.52, porosity=0.12). The results from the aquifersalinity confirms that the higher the salinity of the aquifer the higher the natural gas productionand the lower the produced water as seen in the gwr vs time graph. there was a productionincrease of about 50% when 0 wt% salt encroached the reservoir compared to when 10 wt%Nacl. With this leading finding, a better characterisation of the natural gas reservoir will becarried out for adequate evaluation of the performance of the reservoirs in the phase II of thestudy.Consequently, 75.9132 MMSTB of oil and 2,188.54 BCF of gas was obtained from reservoirsimulation, do nothing case: an additional recovery for the field is about 30.23MMSTB and27.8BSCF of oil and gas respectively. case 1: an additional recovery for the field was about37.21MMSTB and 26.0BSCF of oil and gas respectively. STOOIP of 1548.297365 MMSTBand GIIP of 3007862.483 MMSCF from volumetric, EUR of 52261BSCF gas and EUR of452.6MMSTB from decline curve analysis, and GIIP of 370.47MMSCF and STOOIP of377.26MMSTB from material balance. the volume of initial hydrocarbon obtained frommaterial balance analysis and static model volume estimates are comparable and within 2 -6%difference. The declining curve analysis and production performance analysis were carried outand compared with a slight variation of the end volumes.This study has utilised dynamic reservoir data integrated with various models, which can bevaluable in improving reserve estimation using multiple models compared to single modelsadopted by many research and industry practices.

Level dc:type.qualificationlevel

Doctoral (Level 8)

Year dc:date.issued

2019

Author dc:creator

• Saidu, B

Language dc:language

en

Identifier

oai:salford-repository.worktribe.com:1362942

Author Identifier

0000-0002-7272-0694

OAI identifier oai:identifier

oai:salford-repository.worktribe.com:1362942