Log Permeability Research Articles

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: Influence of matrix porosity, matrix permeability, and fracture coating minerals

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ( 3HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient ( D m/ D ⁎). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of ( D m/ D ⁎) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log( D m/ D ⁎) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log( D m/ D ⁎) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.

Characterization of the velocity field organization in heterogeneous media by conditional correlation

The purpose of the present work is to quantify the correlation structure of simulated velocity fields in heterogeneous permeability fields and to discuss how to represent it in upscaled transport models. We investigate the velocity field correlation structure for multinormal log permeability fields. The simulated velocity distributions are analyzed in a Lagrangian framework, i.e., along the particles' paths. To quantify the different spatial organization of low‐ and high‐velocity zones, we condition the estimated velocity correlation length and time on the initial particle velocity. The velocity correlation length is found to increase with the initial particle velocity, following a power law. Such an effect is likely due to the channeling of high‐velocity zones, which implies that particles keep memory of their initial velocity over longer distances for high initial velocities than for low initial velocities. Two distinct regimes are identified for the velocity correlation time. For low initial particle velocity the correlation time is controlled by the large time needed to escape from the low‐velocity zones. For high initial particle velocity it is controlled by the large time needed for particles to sample the whole velocity field, in particular low‐velocity zones. One of the consequences of these results is that for such velocity fields the nonlinear dependence of both the correlation length and time on the particle initial velocity restricts the use of spatial or temporal Markovian assumptions for modeling velocity transitions in effective transport models.

Comment on “Spatial correlation of permeability in cross‐stratified sediment with hierarchical architecture” by Robert W. Ritzi, Zhenxue Dai, David F. Dominic, and Yoram N. Rubin

Comment on “Spatial correlation of permeability in cross‐stratified sediment with hierarchical architecture” by Robert W. Ritzi, Zhenxue Dai, David F. Dominic, and Yoram N. Rubin

Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff

Previous application of maximum likelihood Bayesian model averaging (MLBMA, Neuman (2002, 2003)) to alternative variogram models of log air permeability data in fractured tuff has demonstrated its effectiveness in quantifying conceptual model uncertainty and enhancing predictive capability (Ye et al., 2004). A question remained how best to ascribe prior probabilities to competing models. In this paper we examine the extent to which lead statistics of posterior log permeability predictions are sensitive to prior probabilities of seven corresponding variogram models. We then explore the feasibility of quantifying prior model probabilities by (1) maximizing Shannon's entropy H (Shannon, 1948) subject to constraints reflecting a single analyst's (or a group of analysts') prior perception about how plausible each alternative model (or a group of models) is relative to others, and (2) selecting a posteriori the most likely among such maxima corresponding to alternative prior perceptions of various analysts or groups of analysts. Another way to select among alternative prior model probability sets, which, however, is not guaranteed to yield optimum predictive performance (though it did so in our example) and would therefore not be our preferred option, is a minimum‐maximum approach according to which one selects a priori the set corresponding to the smallest value of maximum entropy. Whereas maximizing H subject to the prior perception of a single analyst (or group) maximizes the potential for further information gain through conditioning, selecting the smallest among such maxima gives preference to the most informed prior perception among those of several analysts (or groups). We use the same variogram models and log permeability data as Ye et al. (2004) to demonstrate that our proposed approach yields the least amount of posterior entropy (residual uncertainty after conditioning) and enhances predictive model performance as compared to (1) the noninformative neutral case in which all prior model probabilities are set equal to each other and (2) an informed case that nevertheless violates the principle of parsimony.

Transport of Organic Solutes through Amorphous Teflon AF Films

Fluorous media have great potential for selective extraction (e.g., as applied to organic synthesis). Fluorous polymer films would have significant advantages in fluorous separations. Stable films of Teflon AF 2400 were cast from solution. Films appear defect-free (SEM; AFM). Rigid aromatic solutes are transported (from chloroform solution to chloroform receiving phase) in a size-dependent manner (log permeability is proportional to -0.0067 times critical volume). Benzene's permeability is about 2 orders of magnitude higher than in comparable gas-phase experiments. The films show selectivity for fluorinated solutes in comparison to the hydrogen-containing control. Transport rates are dependent on the solvent making up the source and receiving phases. The effect of solvent is, interestingly, not due to changes in partition ratio, but rather it is due to changes in the solute diffusion coefficient in the film. Solvents plasticize the films. A less volatile compound, -COOH-terminated poly(hexafluoropropylene oxide) (4), plasticizes the films (T(g) = -40 degrees C). Permeabilities are decreased in comparison to 4-free films apparently because of decreased diffusivity of solutes. The slope of dependence of log permeability on critical volume is not changed, however.

Predicting Permeability in Un-Cored Intervals/Wells Using Hydraulic Flow Unit Approach

Abstract Prediction of permeability in un-cored intervals/wells is necessary to developing an effective reservoir characterization program and providing information on various depositional and diagenetic controls on pore geometry. Permeability can be obtained from well tests, core analysis, and well logs. Usually using well log data to derive estimates of permeability is the cheapest source. In this paper, routine core analysis and well log data of an actually existing sandstone reservoir in the Gulf of Suez (Egypt) were used to develop permeability correlations using a Hydraulic Flow Unit Approach (HFU). The core data were statistically treated for identification of Hydraulic Flow Units. This involves the calculations of Reservoir Quality Index (RQI), Flow Zone Indicator (FZI), and Pore Level Heterogeneity Index (PLHI). Results showed that six HFUs were identified from core data and each unit has its own FZI. A correlation between FZI calculated from core data and that obtained from well log data was developed for estimating permeability in un-cored intervals/wells. Application of the Pore Level Heterogeneity Index concept to the data determined the existence of six rock types in the studied reservoir. Introduction Estimating permeability in un-cored intervals/wells is a generic problem common to all reservoir engineers. Most of the field-scale reservoir characterization studies require detailed knowledge of petrophysical properties at the drilled wells. Since most wells are not cored, an accurate calculation method of permeability in uncored wells from log data is needed for achieving a realistic reservoir description. Several investigators(1–4) have proposed traditional approaches for permeability estimation. The approaches were based on linear regression or empirical inferences that use correlations among various well log responses. The empirically inferred models are locally applied because there may be large differences in depositional characteristics at other locations. The regression models assume that a linear relationship between logarithmic permeability and porosity exists. Another linear relationship between core porosity and log porosity was also proposed by Canas et al.(5). Both methods ignore the scatter of the data around the fitted line and attribute any scatter to measurement errors. A more reasonable technique is to employ the concept of Hydraulic Flow Units (HFUs) in predicting permeability and reservoir Description(6–12). The term Hydraulic Flow Unit is defined as a representative element volume of the total reservoir rock within which geological and petrophysical properties that affect fluid flow are internally consistent and predictably different from properties of other rock HFUs. Generally, permeability calculations using HFUs offer improved estimations over traditional regression-based averaged relationships. The extent of improvement depends mainly on the geological characteristics of the formation, with larger enhancements achieved in more heterogeneous deposits. In the present study, 510 measurements of porosity and permeability of different sandstone rocks, obtained from an oil reservoir existing offshore of Egypt (Gulf of Suez) were used to develop correlations for in situ permeability estimations. Statistical examination of the developed correlations shows a good agreement between the measured and calculated data.

Automatic History Matching in a Bayesian Framework, Example Applications

SummaryThe Bayesian framework allows one to integrate production and static data into an a posteriori probability density function (pdf) for reservoir variables (model parameters). The problem of generating realizations of the reservoir variables for the assessment of uncertainty in reservoir description or predicted reservoir performance then becomes a problem of sampling this a posteriori pdf to obtain a suite of realizations. Generation of a realization by the randomized-maximum-likelihood method requires the minimization of an objective function that includes production-data misfit terms and a model misfit term that arises from a prior model constructed from static data. Minimization of this objective function with an optimization algorithm is equivalent to the automatic history matching of production data, with a prior model constructed from static data providing regularization. Because of the computational cost of computing sensitivity coefficients and the need to solve matrix problems involving the covariance matrix for the prior model, this approach has not been applied to problems in which the number of data and the number of reservoir-model parameters are both large and the forward problem is solved by a conventional finite-difference simulator.In this work, we illustrate that computational efficiency problems can be overcome by using a scaled limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm to minimize the objective function and by using approximate computational stencils to approximate the multiplication of a vector by the prior covariance matrix or its inverse. Implementation of the LBFGS method requires only the gradient of the objective function, which can be obtained from a single solution of the adjoint problem; individual sensitivity coefficients are not needed. We apply the overall process to two examples. The first is a true field example in which a realization of log permeabilities at 26,019 gridblocks is generated by the automatic history matching of pressure data, and the second is a pseudofield example that provides a very rough approximation to a North Sea reservoir in which a realization of log permeabilities at 9,750 gridblocks is computed by the automatic history matching of gas/oil ratio (GOR) and pressure data.

Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff

Hydrologic analyses typically rely on a single conceptual‐mathematical model. Yet hydrologic environments are open and complex, rendering them prone to multiple interpretations and mathematical descriptions. Adopting only one of these may lead to statistical bias and underestimation of uncertainty. Bayesian model averaging (BMA) [Hoeting et al., 1999] provides an optimal way to combine the predictions of several competing models and to assess their joint predictive uncertainty. However, it tends to be computationally demanding and relies heavily on prior information about model parameters. Neuman [2002, 2003] proposed a maximum likelihood version (MLBMA) of BMA to render it computationally feasible and to allow dealing with cases where reliable prior information is lacking. We apply MLBMA to seven alternative variogram models of log air permeability data from single‐hole pneumatic injection tests in six boreholes at the Apache Leap Research Site (ALRS) in central Arizona. Unbiased ML estimates of variogram and drift parameters are obtained using adjoint state maximum likelihood cross validation [Samper and Neuman, 1989a] in conjunction with universal kriging and generalized least squares. Standard information criteria provide an ambiguous ranking of the models, which does not justify selecting one of them and discarding all others as is commonly done in practice. Instead, we eliminate some of the models based on their negligibly small posterior probabilities and use the rest to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. We then average these four projections and associated kriging variances, using the posterior probability of each model as weight. Finally, we cross validate the results by eliminating from consideration all data from one borehole at a time, repeating the above process and comparing the predictive capability of MLBMA with that of each individual model. We find that MLBMA is superior to any individual geostatistical model of log permeability among those we consider at the ALRS.

Seismic imaging of reservoir flow properties: Time‐lapse pressure changes

Time‐lapse fluid pressure and saturation estimates are sensitive to reservoir flow properties such as permeability. In fact, given time‐lapse estimates of pressure and saturation changes, one may define a linear partial differential equation for permeability variations within the reservoir. The resulting linear inverse problem can be solved quite efficiently using sparse matrix techniques. An application to a set of crosswell saturation and pressure estimates from a CO2 flood at the Lost Hills field in California demonstrates the utility of this approach. The pressure and saturation estimates are mapped into reservoir permeability variations between the boreholes. The resulting permeability estimates agree with a permeability log in an adjacent well and are in accordance with water and CO2 saturation changes imaged in the interwell region.

Oxygen permeability and free volume hole size in ethylene–vinyl alcohol copolymer film: temperature and humidity dependence

Relationship between oxygen permeability and free volume hole size evaluated from ortho-positronium lifetime in ethylene–vinyl alcohol copolymer (EVOH) was studied as functions of temperature and relative humidity. As the relative humidity rises at room temperature, the permeability first decreases and then increases. This behavior is attributed to the effects of pore filling and plasticization by water molecules. Linear correlations are obtained on the plots of logarithmic permeability versus reciprocal free volume hole size for EVOH at different temperatures and humidities as well as for different polymers including EVOH at room temperature, suggesting that the free volume hole size plays a crucial role in the oxygen permeation in EVOH and other polymers.

In situ mineralogy and permeability logs from downhole measurements: Application to a case study in chlorite‐coated sandstones

Well‐logging techniques provide continuous profiles of various in situ physical properties like the bulk density, the photoelectric effect, and the natural gamma radioactivity of geological formations. Our purpose is to use this information to determine a continuous profile of the mineralogy with depth. The well‐log derived mineralogy is then combined with a petrophysical model to infer continuous permeability and saturation profiles in chlorite‐bearing sandstone formations. Our mineralogical inversion algorithm combines a cluster analysis of the raw data and their inversion using the generalized nonlinear inverse method developed by Tarantola and Valette [1982]. A field case is treated concerning a borehole intersecting an alternation of sandstones and shales. The mineralogical logs we obtained are in very good agreement with the mineral proportions measured independently on core samples. Mineralogical profiles are combined with a specific textural model to derive a continuous profile of permeability. We found a very good agreement between this computed permeability log and independent core permeability measurements over 3 orders of magnitude.

Permeability evolution during progressive development of deformation bands in porous sandstones

Triaxial deformation experiments were carried out on large (0.1 m) diameter cores of a porous sandstone in order to investigate the evolution of bulk sample permeability as a function of axial strain and effective confining pressure. The log permeability of each sample evolved via three stages: (1) a linear decrease prior to sample failure associated with poroelastic compaction, (2) a transient increase associated with dynamic stress drop, and (3) a systematic quasi‐static decrease associated with progressive formation of new deformation bands with increasing inelastic axial strain. A quantitative model for permeability evolution with increasing inelastic axial strain is used to analyze the permeability data in the postfailure stage. The model explicitly accounts for the observed fault zone geometry, allowing the permeability of individual deformation bands to be estimated from measured bulk parameters. In a test of the model for Clashach sandstone, the parameters vary systematically with confining pressure and define a simple constitutive rule for bulk permeability of the sample as a function of inelastic axial strain and effective confining pressure. The parameters may thus be useful in predicting fault permeability and sealing potential as a function of burial depth and fault displacement.

Optimizing the Perforating Strategy in Well Completions To Maximize Productivity

Summary The Britannia field is a gas-producing reservoir operated jointly by Chevron and Conoco. Before completion of the wells, the major concern was the optimum underbalance to obtain zero perforation skin during completion. Theoretical models were used to predict the optimum underbalance based on log-derived formation properties. With detailed log permeability data, numerous simulations were carried out to choose the gun, charges, shot density, and perforating strategy for optimum productivity. Different shot densities and charges were used in different sections of the formation based on simulation results, as opposed to choosing perforation parameters based on average well properties. Experiments were conducted to confirm the theoretical underbalance predictions at high underbalance pressures. Reservoir and outcrop core samples were perforated at simulated downhole conditions in the laboratory at different underbalances based on values obtained from the model. Flow performance evaluation of the perforated reservoir core samples confirmed earlier conclusions on the sensitivity of the formation to aqueous wellbore fluids (brine). An underbalance value of 1,000 psi used in the outcrop sample tests indicated near-zero perforation skin. A perforation strategy for the North Sea field was chosen based on the results from this study. Well performance analyses of 12 of the wells completed indicate low to negative skins. The information is presented in this paper as a case of how to design a good perforating job and also to emphasize the need to study optimum underbalance for gas formations.

Stochastical analysis of surfactant-enhanced remediation of denser-than-water nonaqueous phase liquid (DNAPL)-contaminated soils.

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.

Stochastical Analysis of Surfactant-Enhanced Remediation of Denser-than-Water Nonaqueous Phase Liquid (DNAPL)–Contaminated Soils

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid–contaminated soils with spatial variability and heterogeneity.

Quantitative structure-toxicity relationships using TOPS-MODE. 3. Structural factors influencing the permeability of commercial solvents through living human skin

The permeability of a series of 12 commercial solvents through living human skin were studied by using a topological sub-structural approach (TOPS-MODE). We first analyzed the influence of several physicochemical parameters used in describing the skin permeability of the solvents. No single significant relationship was found between any of these physicochemical properties and the permeability of the solvents. A QSAR model using TOPS-MODE descriptors was obtained and validated. This model accounted for more than 95% of the variance in the experimental permeability of these solvents. Using the derived model, the structural factors responsible for the permeability of this series of solvents through living human skin were identified. Methyl groups bonded to heteroatoms or to CH 2 groups resulted in the greatest contributions to skin permeability and these groups were considered to be "permeability enhancers". In contrast, groups of the type X=O (X=S, C) were found to be "permeability inhibitors" because they possessed negative contributions to the logarithm of permeability in all of the studied solvents. Drawing on the idea of permeability "enhancers" and "inhibitors", we hypothesized that the solvents needed to orientate themselves in front of the stratum corneum layer first before penetrating through the skin.

Unstable density‐driven flow in heterogeneous porous media: A stochastic study of the Elder [1967b] “short heater” problem

The situation of a dense fluid overlying a lighter one is potentially unstable and under certain conditions may result in fingers of dense contaminant freely convecting downward. Free convection causes increased contaminant transport over larger distances and over shorter timescales than is possible by diffusion alone. Unlike free convection in homogenous porous media, free convection in heterogeneous porous media has received relatively little attention. In this study, a well‐understood problem of transient free convection in homogeneous porous media, theElder [1967b] “short heater” problem has been modified to study the effects of heterogeneity in permeability distributions on solute transport processes using a stochastic framework. A set of measurable indicator characteristics including solute fluxes, solute present, center of gravity and finger penetration depth are used in the quantitative analysis of output. Heterogeneity in the permeability distribution provides both the triggering mechanism for the onset of instabilities and also controls their subsequent growth and/or decay. Results show that (1) an increase in the standard deviation of the log permeability field results in a greater degree of instability at earlier times but promotes stability at later times, (2) an increase in the horizontal correlation length of the log permeability field creates laterally extensive low‐permeability zones that dissipate upward and downward motion needed to maintain convection and therefore causes a reduction in the degree of instability, (3) a greater degree of heterogeneity causes greater uncertainty in predictions, and (4) traditional predictive methods such as the Rayleigh number (based upon an average permeability) do not generally work in their application to heterogeneous systems. Probability of exceedence analysis also demonstrates that analyses based upon homogeneous assumptions will typically underestimate, often quite significantly, the value of key measurable characteristics.

Fluid saturation from well logs using committee neural networks

Neural computing has made a major step forward by the introduction of multi-net systems in practical applications. In this study we developed and tested a modular artificial neural network system for predicting underground fluids, water, oil and gas, and their partial saturations, directly from well logs, without explicit knowledge of the fluid and rock properties as required by conventional methods. Based on laboratory data on relative permeability for alternative fluid systems –oil–water or gas–oil – respectively, relative permeability logs may also be provided for input to reservoir simulation while drilling. Simple three-layer back-propagation artificial neural networks (ANN) constitute the building blocks of a modular system, where the input logs are sonic, density, neutron porosity and resistivity. By numerical experiments using synthetic logs we have determined the optimal architecture of the ANN. We find that the overtraining strategy is a suitable technique for bias reduction and an unconstrained optimal linear combination is the best method of combining outputs in the committee neural net. The accuracy of the net is restricted only by accuracy of data. Comparison between ANN predictions of fluid saturation with those of conventional petrophysical analysis, in wells unknown to the network, indicates a standard error of less than 0.03.

AN INTEGRATED PETROPHYSICAL WORKFLOW TO GENERATING FLUID SUBSTITUTED LOGS FOR AVO CHARACTERISATION—GIPSY AND NORTH GIPSY FIELDS CASE STUDY, NORTH WEST SHELF, AUSTRALIA

As part of a multi-well field study an integrated petrophysical workflow was developed to include the generation of fluid substituted logs for AVO characterisation.The workflow relied upon the construction of a multimineral model that best approximated the actual mineral content of the reservoir. Any limitations or assumptions were noted and taken into account when creating the multi-mineral model. Other petrophysical results were derived from the same model to validate its consistency such as intrinsic permeability, porosity, water saturation, etc. Iteration between the model and the results was required until a consistent model was achieved.The estimation of an intrinsic permeability log was based upon the k-Lambda method that uses the multimineral model and porosities.The estimation of a shear slowness log and the fluid substituted logs was based upon elastic rock properties derived from the multi-mineral model and the acquired compressional slowness log and bulk density log. This integrated approach provides a higher confidence in the derived results, which are then used as input into the reservoir model, thereby improving the reserve calculations.The interdependence of each derived result on the same input multi-mineral model ensures consistency and predictability in a complex geological environment, which captures all available information.The method is demonstrated with the Gipsy–1 and North Gipsy–1 wells, which were part of the original field study.

Reservoir Heterogeneities, in Fractured Fluvial Reservoirs of the Buchan Oilfield (Central North Sea)

The Buchan Oilfield in the central North Sea is a structurally complex, pervasively fractured Upper Devonian-Carboniferous reservoir comprising vertically stacked, sandstone-dominated, fining-upward sequences deposited predominantly by braided streams. Hierarchical analysis of reservoir quality at the microscale (thin sections), mesoscale (lithofacies and facies sequences) and megascale (zones composed of more than one mesoscale sequence) levels shows that the reservoir can be divided into six megascale units based on their sedimentological properties, poroperm values and electric log response. The microscale and mesoscale properties of these units, particularly the presence of fractures and variations in the correlation coefficient between the logarithm of permeability and porosity, provide a means of defining effective and non-effective reservoir zones, which correspond with, or occur within the units. The most effective zone, between 2738 and 2788 m, consists predominantly of extensively fractured subarkoses which differ from other sandstones in the reservoir in that they contain more preserved primary intergranular porosity and secondary fracture porosity, with porosity values up to 30. 2%, and permeabilities up to 1475 mD. This zone extends across most of the field where it defines, more precisely than has previously been possible, the best quality and most productive part of the reservoir section.