Carbonate reservoir characterization and fluid quantification seem more challenging than those of sandstone reservoirs. The intricacy in the estimation of accurate hydrocarbon saturation is owed to their complex and heterogeneous pore structures, and mineralogy. Traditionally, resistivity-based logs are used to identify pay intervals based on the resistivity contrast between reservoir fluids. However, few pay intervals show reservoir fluids of similar resistivity which weaken reliance on the hydrocarbon saturation quantified from logs taken from such intervals. The potential of such intervals is sometimes neglected. In this case, the studied reservoir showed low resistivity. High water saturation was estimated, while downhole fluid analysis identified mobile oil, and the formation produced dry or nearly dry oil. Because of the complexity of Lowresitivity pay (LRP) reservoirs, its cause should be determined a prior to applying a solution. Several reasons were identified to be responsible for this phenomenon from the integration of thin section, nuclear magnetic resonance (NMR) and mercury injection capillary pressure (MICP) data-among which were the presence of microporosity, fractures, paramagnetic minerals, and deep conductive borehole mud invasion. In this paper, we integrated various information coming from geology (e.g., thin section, X-ray diffraction (XRD)), formation pressure and well production tests, NMR, MICP, and Dean-Stark data. We discussed the observed variations in quantifying water saturation in LRP interval and their related discrepancies. The nonresistivitybased methods, used in this study, are Sigma log, capillary pressure-based (MICP, centrifuge, and porous plate), and Dean-Stark measurements. The successful integration of these saturation estimation methods captured the uncertainty and improved our understanding of the reservoir properties. This enhanced our capability to develop a robust and reliable saturation model. This model was validated with data acquired from a newly drilled appraisal well, which affirmed a deeper free water level as compared to the previous prognosis, hence an oil pool extension. Further analysis confirmed that the major causes of LRP in the studied reservoir were the presence of microporosity and high saline mud invasion. The integration of data from these various sources added confidence to the estimation of water saturation in the studied reservoir and thus improved reserves estimation and generated reservoir simulation for accurate history matching, production forecasting, and optimized field development plan.
Characterization and fluid quantification of Carbonate reservoirs looks more challenging than those of sandstone reservoirs. The determination of accurate hydrocarbon saturation is more tasking due to their complex and heterogeneous pore structures, and mineralogy. Traditionally, resistivity logs are used to identify pay intervals due to the resistivity contrast between oil and water. However, when pay intervals exhibit low resistivity, such logs exhibit low confidence in the precise determination of the hydrocarbon saturation. Few Middle-Eastern reservoirs are categorized as low resistivity pay, where resistivity based log analysis results in high water saturation. However, downhole fluid analysis identifies mobile oil, and the formation flows dry or nearly dry oil during production tests. This makes resistivity based saturation computation questionable. Because of the complexity of low resistivity pay (LRP), its cause should be determined prior to applying a solution. Several reasons were identified to be responsible for this phenomenon- among which are the presence of micro-porosity, fractures, paramagnetic minerals, and deep conductive borehole mud invasion. Integration of Thin section, Nuclear magnetic resonance (NMR) and Mercury injection capillary pressure (MICP) data from the studied formation indicated the presence of micropores network. This paper discusses the observed variations in quantifying water saturation in LRP interval and the related discrepancies between the resistivity and non-resistivity based techniques. The non-resistivity based methods, used in the course of this study, are coined from sigma log measurement and core data, either capillary pressure-based (MICP, Centrifuge, and Porous plate), or direct from Dean-Stark measurements. The interpretation process considered water saturation derived from resistivity measurement and core data combined with production test information. The combination of several water saturation determination approaches captured the uncertainty and improved our understanding of the reservoir properties. This enhanced our capability to develop a robust and reliable saturation model. The integration of data from these various sources added confidence to the estimation of water saturation in the studied field and thus, improved reserves estimation and reservoir simulation for accurate history matching, production forecasting and optimized field development plan.
Early identification of low resistivity pay (LRP) reservoir is vital in assessing its prospect and capability. Productive reservoirs may exhibit low resistivity and consequently, their potential is simply overlooked. Remapping these intervals can have significant production and reserve implications. Traditionally, resistivity logs are used to identify pay intervals due to the resistivity contrast between oil and formation water. However, when pay intervals exhibit low resistivity, such logs return low confidence in defining hydrocarbon potential. Due to the complexity of low resistivity pay (LRP), its cause and proper mitigation should be determined prior to applying a solution. Researchers have identified several reasons responsible for this occurrence; among which are the presence of heterogeneous pore structures specifically micro-porosity, fractures, paramagnetic minerals, and deep conductive mud invasion. Almost all preceding publications assume a technique will work but not the other. However, this is the first time, to our knowledge; an integrated approach is used to develop LRP assessment workflow. We have integrated the information coming from geology (e.g., thin-section, XRD), formation pressure and well tests, NMR, MICP, and dean stark data. The integration successfully identified and remapped the carbonate low resistivity reservoir. This model was validated in an appraisal well on Abu Dhabi mainland, for that an extended data was acquired. Thereafter, the integrated LRP model was compared with the computed water saturation from conventional resistivity tools. The validation was successful in terms of confirming the prognosis. Interpreting the results from the multidisciplinary integrated model confirms a deeper Free Water Level (FWL), hence oil pool extension. Further analysis showed that the causes of LRP in this considered formation was limited to presence of micro-porosity and high saline mud invasion.
Pulse neutron capture (PNC) is an effective technique to monitor lateral and vertical saturation/sweep. Assessing pulsed neutron results in either open-hole (OH) or cased-hole (CH) is key in evaluating formation properties, while with reservoir performance routinely monitored, time lapse logs are compared with the base logs to dynamically assess saturation changes and sweep efficiency. PNC sensitivity to factors such as invasion, bore-hole and cement; makes its result influenced by rock matrix and fluid properties. LWD logging may minimize the mud filtrate impact; however this is subject to the drilling parameters and exposure. LWD PNC has been analysed (drill and wipe pass) in both oil and water base muds. Quality assessment is performed on LWD/WL Sigma considering: mud used, invasion, formation water and mud properties. Variable Sigma was used to improve PNC saturation interpretation particularly within the transition zone. The effect of mud was discussed with examples showing its impact on data properties. WL PNC time lapse logging over five years were analysed, results indicated mud dissipation process masking formation response. Resistivity and pulse neutron saturations are compared. PNC saturation is integrated with resistivity based saturation. The capability of the pulsed neutron logging to derive meaningful results within the studied fields were examined in both OH, and CH conditions along with the definition of base log and the parameters used to derive saturation. Variable Sigma concept and uncertainty within transition zone is discussed. The used methodology and integration has improved the interpreted saturation, consequently enhanced the reservoir management. The data used within the paper comes from two different carbonate fields' of complex, heterogeneous pore structures, and diverse mineralogy, allowing generic approach to the drawbacks seen.
To appraise hydrocarbon and its properties of a low permeability formation within deep Baram delta reservoirs. Formation X is low permeability silty sandstone. It forms along other formations stacked sandy shale reservoirs. The stacked formations are interpreted as Hydrocabon bearing formations based on the openhole and pressure data. However, the reservoir in question, showed features different from the adjacent reservoirs. This manuscript appraises the reservoir and illustrates the workflow followed to identify its fluid type and the best method to produce the hydrocarbon. Triple combo logs identified formation X as hydrocarbon bearing with low permeability and low porosity. Formation pressures gradients indicated the formation to be oil; however, the bottom hole sample, when pumped out, indicated alternating of oil and gas despite the low differential pressure. During the PVT measurement the sample was first re-pressurised until a single phase was achieved and it was then subjected to Differential Liberation and Constant Composition Experiments (CCE). These experiments showed the Bubble Point pressure of the sample to be higher than the reservoir pressure, thereby indicating two mobile phases in the reservoir and the probability of a Gas-Oil Contact (GOC). The Experiments were also successfully simulated and matched using the Peng Robinson Equation of State. The Laboratory experiments directly contradicted the interpretation of Wireline Logs and pressure gradient both of which, indicated single phase light oil. The collected bottom hole sample indicated that both oil and gas are mobile at reservoir level, this finding is supported by PVT laboratory experiments. The Differential Liberation, CCE experiments and EOS fitting demonstrated the fluid to be two Phases at Reservoir Condition where both phases are likely to be mobile. Therefore, it is suspected that the fluid will go from being Gas to Oil with increasing depth without going through GOC, i.e. with continuous compositional grading as is possible for fluids near their critical temperature. This phenomenon could not be captured using open hole conventional logs and therefore the is team is currently investigating the best practice to identify such reservoirs.
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