Most laboratory work in MEOR, both in screening and in development, is performed under in situ temperatures and in brines similar to those of the target reservoir. However, the effect of in situ pore pressures in such work is normally ignored. Much of our understanding of the effects of hydrostatic pressure on microorganisms comes from studies of microbial communities at the ocean floor. Since nearly 90% of the ocean floor has pressures ranging from 10 MPa to over 100 MPa, there is a paucity of data concerning effects on microorganisms at the lower pressures found in many oil reservoirs. In our studies of the indigenous cells from injection brine at the North Burbank Unit, we have found that pressures ranging from 0.1 MPa to 8.8 MPa can have a significant effect on pH changes, substrate utilization, end product formation and permeability reduction. In general, hydrogen ion concentrations and carbohydrate utilization rates increased with increasing pressures. Methanol was found to be a significant end-product in the presence of hydrostatic pressure but found to be absent under atmospheric conditions. The fact that some of the observed effects could be demonstrated by simply reducing the gas headspace suggests that gas solubility could be an important factor. Gas formation in a core was estimated to account for as much as 50% of the permeability decrease observed in cores run under atmospheric pressure. Therefore the changes observed are of such magnitude as to alter the MEOR process in the reservoir from that indicated by laboratory studies not done under pressure. Our results strongly suggest that all MEOR studies pertaining to a known reservoir should be evaluated under the in situ conditions of the reservoir, including pressure.
Sisi and Nubi (SNB) fields are two adjacent primarily gas fields located 25 km offshore from the modern Mahakam delta These fields are complex from a reservoir management point of view with hundred thousands of Static & dynamic data, and continuously increase by time. Reservoir synthesis and geomodel update are always on-going process with numerous QC, data mining & data manipulation. In brief, Sisi Nubi data management & synthesis challenges are: (1) Enormous size of static & dynamic data (2) Numerous Data mining & data manipulation (3) Rigorous Geomodel QC and reporting. Business Intelligence (BI) is the philosophy of this study; it is a set of techniques and tools for the acquisition and transformation of raw data into meaningful and useful information for business analysis purposes. The goal of BI is to allow for the easy interpretation of these large volumes of data. The Sisi Nubi dashboard is a self-service business intelligence tool that was design by the asset to answer & streamline the database management and reporting, hence give more time for the asset's geosciences team to do the reservoir synthesis and optimize the study time by automate the data mining & manipulations. The Sisi Nubi dashboards composed of an automated workflow in the geomodeling platform for the data mining, combined with spreadsheet based tool for the data manipulation and presentation (dashboard-ing). The result of this study presented in 6 unique dashboards, representing 6 difference perspectives of the user. These dashboards are linked to the SNB geomodel and allow instantenous update. Combined with the updated SNB geomodel workflow, the collaboration of two tools has proven significantly streamline the geomodeling reporting & synthesis efficiency.
Sisi-Nubi (SNB) is a gas field located 25 km offshore from the modern Mahakam delta with overpressure reservoirs being found typically in the Sisi Main Zone (SMZ) interval. SNB 3D seismic data indicates a velocity reversal in the SMZ interval, where the overpressure occurs. This velocity reversal has a relation with location of shelf break (distal area), where beyond shelf break the NTG value is sharply decreased. In the Mahakam area, overpressure gas reservoirs are one of the main issues in terms of drilling hazards. This has been historically managed by integrating surrounding wells' pressure data to predict the pore pressure profile that would be expected in an upcoming well. In new areas or where pressure data is lacking, it is difficult to predict the PP which can result either in heavier than necessary well architectures or an increased risk of taking a kick. An integrated pore pressure study has been carried out on the SNB field in order to provide three dimensional and spatially continuous pore pressure prediction using four different disciplines: sedimentology, reservoir geology, geophysics and geomechanics. The integrated pore pressure model over SNB is contained within a 3D geological model where the Eaton equation can be run using following datasets: sonic well data and sedimentological trend (Well Driven model), upscaled/resampled seismic interval velocity (seismic driven model) and hybrid method as compromise between two data sources involves using the seismic data as a soft trend for the extrapolated well data (hybrid model). Based on the blind well test analysis, the hybrid methodology shows the best result in terms of precision and 3D distribution and allows a continuous prediction of pore pressures even where there is poor well control. However, the others two methodologies could be used as an alternative when the available data is limited. This methodology gives a new approach with more integrated information in 3D pore pressure modeling that improved the classic pore pressure prediction in field Scale and/or basin scale. However, with the remaining uncertainty and discrepancy between the DT well scale velocity and the DT seismic velocity, and considering all detail well events important inputs (Gas evolution including long connection tests, kick, pressure test, HC bouyancy and other drilling events), collaboration with a strong 1D Pore Pressure synthesis will give a comprehensive result.
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