We find the formula σ=φm[σω+AQv/ (1+CQv/σw)] that embodies the fact that the rock conductivity σ is a nonlinear function of water conductivity σw, can fit data on 140 cores rather well with m≊2, A=1.93×m (mho/m)(l/mol) and CQv=0.7 (mho/m). The observed curvature at low salinity is due to an interplay of tortuosity and water conductivity. Empirical correlation shows that m increases with the clay content, as the tortuosity increases with the clay content. Thus, the conductivity of a fully water saturated clay bearing (shaly) sand is completely determined from porosity φ, charge density Qv, and water conductivity σw.
Low porosity fractured reservoirs have been successfully described using a combination of high resolution geometrical information from borehole images together with deeper penetrating log evaluation methods. Borehole images from acoustic or electrical scanning tools provide statistics of fracture distribution, first order estimates of fracture opening and porosity, and a basis for geological inference. Their drawback is that, in this environment, the events on the images bear a strong overprint of the drilling process. Deeper penetrating but lower resolution techniques such as Stoneley wave reflectance and deep resistivity log inversion are used to distinguish the deep and permeable fractures that may contribute to flow. By making some assumptions about the nature of the porosity in basement reservoirs we develop a new method to estimate the porosity and the fraction of this porosity due to fractures. This method makes use of the Kuster-Toksoz acoustic scattering model and requires low frequency measurements of compressional and shear velocities. Introduction In their study of the basement reservoirs on the continental shelf off the south coast of Vietnam, Areshev et al. found that the effective porosity was due to three components: fractures of tectonic origin, vugs ("cavernous porosity") of hydrothermal origin and pores caused by near surface weathering. The porosity distribution is very irregular. High porosities tend to be concentrated in breccias associated with large faults, however high porosity intervals are often widely separated by low porosity and permeability intervals. In the White Tiger field average core porosity in the deeper basement sections was less than three percent and divided almost equally into fracture and vugs. Evaluation of reserves from well logs in such conditions is not straightforward. The well in which the logs are acquired samples only a very small part of an irregularly distributed fracture-pore network, and it is by no means obvious whether such a sampling is statistically significant for reserves estimation. At such low overall porosities the error in estimating porosity using conventional porosity logging techniques is close to the measurement itself. Moreover, variations in rock properties, such as density and hydrogen index, and borehole damage, which affects shallow reading devices, can be misinterpreted as changes in porosity. For this reason quantitative estimation of subsurface fracture porosity and fracture permeability has been considered to be highly variable and inaccurate.
This study defines an approach to determine porosity, fluid saturations and permeabilities from wireline log data in sandstone reservoirs containing low salinity formation brines. An extensive set of measurements were made on low invasion core were analyzed to establish the ground truth, and to control the input parameter choices for log analysis. A recently developed water saturation equation, that accounts for the different geometry of the conducting paths along grain surfaces and within the pore fluid, was used to analyze the wireline resistivity logs. This equation predicts far less resistivity contrast between hydrocarbon and water-bearing intervals than other widely used relationships. The log interpretation technique consists of making robust estimates of highly sensitive parameters such as the cation exchange molarity, QV, and paying attention to the details in the estimation of the true formation resistivity, Rt and the formation resistivity factor, F. Introduction The determination of hydrocarbon saturation from resistivity logs in low salinity sandstone reservoirs is one of a class of problems referred to in the literature as "low (resistivity) contrast pays". Interpretation difficulties arise principally because the conductivity of the grains (related to shaliness) is as important as the conductivity of the formation water, and the conditions for the Archie formulae to relate resistivity solely to water saturation no longer apply. The problem is compounded by the difficulty of precisely estimating the shaliness from well log data. Slight changes in the estimates of shaliness can result in large changes in the derived values of saturation. There are numerous shaly-sand saturation equations in the literature: these can be loosely divided into two types of models: the Vsh (shale volume) models, and; the double layer (surface conductance) models. Hill and Milburn were amongst the first to relate the CEC (cation exchange capacity) to the effective shaliness. Waxman, Smits and coworkers developed this idea into a model (the "WS" model) which has gained widespread acceptance in the industry. The WS model relates the additional conductivity of shaly sands to the cation exchange molarity (or cation exchange capacity per unit pore-volume), QV. In water-filled rocks at high salinities this additional conductivity is proportional to QV: (1)
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