Distribution Of Rock Properties Research Articles

Reservoir characterisation using artificial bee colony optimisation

To obtain an accurate estimation of reservoir performance, the reservoir should be properly characterised. One of the main stages of reservoir characterisation is the calibration of rock property distributions with flow performance observation, which is known as history matching. The history matching procedure consists of three distinct steps: parameterisation, regularisation and optimisation. In this study, a Bayesian framework and a pilot-point approach for regularisation and parameterisation are used. The major focus of this paper is optimisation, which plays a crucial role in the reliability and quality of history matching. Several optimisation methods have been studied for history matching, including genetic algorithm (GA), ant colony, particle swarm (PS), Gauss-Newton, Levenberg-Marquardt and Limited-memory, Broyden-Fletcher-Goldfarb-Shanno. One of the most recent optimisation algorithms used in different fields is artificial bee colony (ABC). In this study, the application of ABC in history matching is investigated for the first time. ABC is derived from the intelligent foraging behaviour of honey bees. A colony of honey bees is comprised of employed bees, onlookers and scouts. Employed bees look for food sources based on their knowledge, onlookers make decisions for foraging using employed bees’ observations, and scouts search for food randomly. To investigate the application of ABC in history matching, its results for two different synthetic cases are compared with the outcomes of three different optimisation methods: real-valued GA, simulated annealing (SA), and pre-conditioned steepest descent. In the first case, history matching using ABC afforded a better result than GA and SA. ABC reached a lower fitness value in a reasonable number of evaluations, which indicates the performance and execution-time capability of the method. ABC did not appear as efficient as PSD in the first case. In the second case, SA and PDS did not perform acceptably. GA achieved a better result in comparison to SA and PSD, but its results were not as superior as ABC’s. ABC is not concerned with the shape of the landscape; that is, whether it is smooth or rugged. Since there is no precise information about the landscape shape of the history matching function, it can be concluded that by using ABC, there is a high chance of providing high-quality history matching and reservoir characterisation.

From outcrop to 3D modelling: a case study of a dolomitized carbonate reservoir, Zagros Mountains, Iran

ABSTRACT Outcrop data derived from fieldwork, remote sensing satellite and LiDAR-derived 3D models were used to build an integrated dual porosity-permeability static reservoir model which captured stratigraphic, diagenetic and structural heterogeneities. The study focuses upon the Mishrif-Mauddud/Sarvak interval, one of the most prolific reservoir units in the Middle East. The study area is exceptionally well exposed in deep gorges which cut transversally across anticlines of the Simply Folded Belt of the Zagros Mountains. The outcrops reveal volumetrically significant dolomitization of the latest Albian to Turonian carbonates of the Lower and Upper Sarvak formations. Three different dolomite bodies, which are spatially connected and genetically linked to the same fluid flow event, were recognized and mapped: (1) a thick dolomite body replacing the Lower Sarvak and forming a massive dolomite core; (2) horizontally extensive stratabound dolomite bodies (sheets), emanating laterally from the massive dolomite; and (3) vertically elongated dolomite pipes, rooted in the massive dolomite and typically replacing slope facies of the Upper Sarvak Formation. The widespread development of tight, non-planar dolomite textures (a typical feature of high temperature dolomitization) drastically reduces the reservoir potential of the dolomitized geobody in the study area. In particular, this is present in the massive dolomitized body. Vuggy porosity seems to increase porosity only locally and to a limited extent, developing a non-connected pore network. The dominant porous dolomite textures are more abundant in the peripheral part of the geobody (dolomite sheets), where they are strongly controlled by precursor facies and diagenesis. Three main dolomite pore types were identified (intercrystalline, interparticle and mouldic), linked to the depositional environment of the precursor limestone. These pore types were used for petrophysical modelling. The approach adopted in this study allowed the distribution of rock properties in the dolomitized geobody to mimic the main depositional facies architecture. The study area is characterized by a simple fracture network. Two main fracture sets and two major sets of conjugate normal faults were recognized in the field and mapped on 3D virtual outcrop data. Non-stratabound fracture density varied according to stratigraphic unit and/or dolomite body type (pipes/massive/sheets), showing a general increase from precursor limestone to dolomite. Fracture density also varied according to distance from faults (fault damage zone). This was particularly true in the limestone. The data also showed a prominent increase in fracture height from limestone to dolomite bodies, indicating that the dolomitized geobodies are likely sites for high production and early water breakthrough.

Numerical modeling of CO2 injection into a typical US Gulf Coast anticline structure

This paper summarizes recent numerical modeling activities investigating geological CO2 sequestration project at the Cranfield field, Mississippi, USA, performed with the commercial compositional flow simulator CMG-GEM. The oilfield was produced from the 1940’s to the 1960’s but has been the recent recipient of an enhanced oil recovery (EOR) CO2 flood. The subset of actual site operations of interest to the BEG consists of (1) an early phase, object of this paper, in which CO2 is injected into the oil-bearing reservoir (the so-called Phase II) and (2) a second phase (started on December 1, 2009) in which CO2 is injected at a high rate (>100 kt/yr for several years) in the saline aquifer down dip of the reservoir (Phase III). We present the modeling efforts related to the early phase of injection (Phase II, started in July 2008) in which CO2 is injected into the oil-bearing reservoir. The objectives of the modeling effort are to (i) to gain insights on how to approach CO2 injection modeling at the site, (ii) to match recent pressure measurements at several wells including a dedicated observation well, and (iii) to vindicate the necessity of monitoring of reservoir pressure. Its intent is not necessarily to do a full-fledged history match of the historical production period (1940’s–1960’s). We conducted numerous repeat simulation runs to modify boundary conditions, fluid properties, and reservoir properties to match observed fluid responses to production and to injection. A good understanding of subsurface heterogeneities, and composition of the oil and gas components, and boundary conditions of the reservoir is the key to successful history matching. However, allocating the correct distribution of rock properties based on historical geophysical logs remained an area of uncertainty even as additional new data were obtained during characterization because of the complex interplay between depositional environment and strong overprint of diagenetic events. Parameters of utmost importance for a correct description of a flow field, in particular the relationship between porosity and permeability and the nature of permeability spatial variations remain uncertain as well as boundary conditions. The uncertainty was dealt with through sensitivity analyses. Ultimately, the constructed model shows a reasonable match with the data.

CSimMDMV: A parallel program for stochastic characterization of multi-dimensional, multi-variant, and multi-scale distribution of heterogeneous reservoir rock properties from well log data

We present CSimMDMV, a software package to simulate two- and three-dimensional, multi-variant heterogeneous reservoir models from well logs at different characteristic scales. Based on multi-variant conditional stochastic simulation, this software is able to parameterize multi-dimensional heterogeneities and to construct heterogeneous reservoir models with multiple rock properties. The models match the well logs at borehole locations, simulate heterogeneities at the level of detail provided by well logging data elsewhere in the model space, and simultaneously honor the correlations present in various rock properties. It provides a versatile environment in which a variety of geophysical experiments can be performed. This includes the estimation of petrophysical properties and the study of geophysical response to the heterogeneities. This paper describes the theoretical basis of the approach and provides the details of the parallel implementation on a Linux cluster. A case study on the assessment of natural gas hydrate amount in Northwest Territories, Canada is provided. We show that the combination of rock physics theory with multiple realizations of three-dimensional and three-variant (3D–3V) gas hydrate reservoir petrophysical models enable us to estimate the average amount of gas hydrate and associated uncertainties using Monte Carlo method.

Role of effective permeability distribution in estimating overpressure using basin modelling

Overpressure generation is a function of the rates of sedimentation, compaction, fluid generation from kerogen and dehydration of minerals, and most importantly the lateral distribution of permeability within a basin as this controls lateral drainage. Sedimentary basins, however, are typically highly heterogeneous with respect to primary sedimentary facies, diagenesis and tectonic development. While fluid flow models based on idealised homogeneous basins may further our understanding of the processes that influence overpressure development, the results are very sensitive to the distribution of rock properties, particularly permeability. The absolute permeability of sedimentary rocks varies from more than 1 Darcy to less than 0.01 nanodarcy (nD) (10 −11 Darcy). Simple calculations, assuming vertical flow and no lateral drainage within the basin, show that overpressures approaching fracture pressure in the overburden will be reached if the effective permeability of the shale forming the seal is less than 0.1–0.01 nD (1.10 −22–1.10 −23 m 2). The permeability of shales varies greatly as a function of primary textural and minnerlogical composition and it is not possible to accurately predict the effective permeability of a sequence of shales forming pressure barriers. Overpressure in uplifted basins, where there is no compaction taking place, can only be maintained over geological time if the permeabilities are much lower. Overpressure is often controlled by lateral drainage but the effective permeabilities for fluid flow across faults and the offset of permeable layers are also difficult to predict. In most cases, uncalibrated basin modelling is unable to accurately predict the magnitude and distribution of overpressures because the vertical and horizontal permeabilities in sedimentary basins cannot be determined in sufficient detail. In basins that have been extensively explored and developed, incorporation of prior geological knowledge into basin models may allow overpressures to be predicted ahead of the drill bit. However, with such a large body of information already gathered about the basin it is debatable what extra value basin modelling is providing to pressure predictions.

Reducing temperature uncertainties by stochastic geothermal reservoir modelling

SUMMARY Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining postprocessing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.

Stochastic evaluation of fluvial to marginal marine sealing facies

Hydrocarbon top seal analyses are particularly difficult in fluvial and marginal marine settings. Although these settings often contain beds comprised of a low-permeability, clay-rich lithology associated with high quality seals, their presence does not guarantee an effective seal because individual beds within the stratal unit may be laterally discontinuous. Lateral facies changes, truncation of fine-grained beds, or the presence of crevasse splays may provide cross-stratal migration pathways, reducing the effective sealing capacity to a magnitude less than the closure height. To evaluate probable bed seal capacities in such a setting, we have calculated 75 statistically equivalent geologic models of a heterogeneous bed seal based upon facies interpretations derived from measured data. Measured capillary and hydraulic properties of rocks in each facies were then fit to Gaussian distributions. We populated the geologic models with flow properties by randomly selecting from these distributions. Two realizations of the rock property distributions were performed for each of the 75 object-based geologic models. Gas charge was simulated in each of the rock property model trials using a percolation-based hydrocarbon migration software program. The results of the simulations return a probability distribution of bed seal capacities, measured in equilibrium gas column heights, from which cumulative frequency diagrams and percentile rankings may be derived. Channel amalgamation by incision juxtaposing levee overbank and/or channel facies formed the most common type of cross-stratal leak point. A factor of 10 difference in the P50 seal capacity was observed by varying the net volume fraction of channels from 10% to 30%. Higher seal capacity realizations were found to have a low density of channels near the structural crest, a variable which outweighs all other stochastic parameters. These results highlight the importance of a risking-based methodology to account for variability in bed seal stratigraphy in fluvial to marginal marine settings.

3D microanalysis of geological samples with nanofocus computed tomography

High resolution CT nowadays is a well established method for numerous industrial applications [Roth et al. 2003; Moller-Gunderson 2007; Nier et al. 2003] as well as for a wide range of research areas [Bonse 2004 and 2006]. During the last decade, Computed Tomography (CT) has progressed to higher resolution and faster reconstruction of the 3D-volume. Most recently it even allows a three-dimensional look into the inside of geological samples with submicron resolution. As shown by Brunke et al. [2008], nanoCT-systems in pursuit of high resolution images, the potential, convenience and economy can now compete in many application fields with high cost and rare available synchrotron facilities. Computed Tomography for geological purposes can lead to a new dimension of understanding of the distribution of rock properties. Especially spatial distribution of pores and pore-connections as well as cementation properties are of utmost importance in the evaluation of reservoir properties. Moreover rock analysis with the aid of X-ray Computed Tomography may lead to better analysis and prediction of well stimulation jobs. For example, a plug can be scanned before and after being stimulated with acid. The possibility to visualize the whole plug volume in a non-destructive way and to use the same plug for further analysis is undoubtedly currently the most valuable feature of this new type of rock analysis and will be a new area for routine application of X-ray Computed Tomography in the near future. The paper will outline the hard- and software requirements for high resolution CT. It will showcase several geological applications which were performed with the nanotom, the first 180 kV nanofocus CT system tailored specifically for highest-resolution scans of samples up to 120 mm in diameter and weighing up to 1 kg with exceptional voxel-resolutions down to <500 nm (<0.5 microns).

Neural network prediction of carbonate lithofacies from well logs, Big Bow and Sand Arroyo Creek fields, Southwest Kansas

In the Hugoton Embayment of southwestern Kansas, St. Louis Limestone reservoirs have relatively low recovery efficiencies, attributed to the heterogeneous nature of the oolitic deposits. This study establishes quantitative relationships between digital well logs and core description data, and applies these relationships in a probabilistic sense to predict lithofacies in 90 uncored wells across the Big Bow and Sand Arroyo Creek fields. In 10 wells, a single hidden-layer neural network based on digital well logs and core described lithofacies of the limestone depositional texture was used to train and establish a non-linear relationship between lithofacies assignments from detailed core descriptions and selected log curves. Neural network models were optimized by selecting six predictor variables and automated cross-validation with neural network parameters and then used to predict lithofacies on the whole data set of the 2023 half-foot intervals from the 10 cored wells with the selected network size of 35 and a damping parameter of 0.01. Predicted lithofacies results compared to actual lithofacies displays absolute accuracies of 70.37–90.82%. Incorporating adjoining lithofacies, within-one lithofacies improves accuracy slightly (93.72%). Digital logs from uncored wells were batch processed to predict lithofacies and probabilities related to each lithofacies at half-foot resolution corresponding to log units. The results were used to construct interpolated cross-sections and useful depositional patterns of St. Louis lithofacies were illustrated, e.g., the concentration of oolitic deposits (including lithofacies 5 and 6) along local highs and the relative dominance of quartz-rich carbonate grainstone (lithofacies 1) in the zones A and B of the St. Louis Limestone. Neural network techniques are applicable to other complex reservoirs, in which facies geometry and distribution are the key factors controlling heterogeneity and distribution of rock properties. Future work involves extension of the neural network to predict reservoir properties, and construction of three-dimensional geo-models.

Modelling fine-scale heterogeneity for optimal history matching from aeolian gas reservoirs, Neptune Field, UKCS

Improved matching of reservoir simulation model results to production data in gas fields allows improved reservoir management and optimization of hydrocarbon production. In high net:gross aeolian sandstones this requires the full range of scales of permeability heterogeneity to be represented in a model. This necessitates the modelling and appropriate upscaling of rock properties, including the millimetre-scale lamina effects within the aeolian dune slipface facies, the contrast between dune apron and slipface facies and the impact of first- and second-order bounding surfaces within the dune complexes and the super-bounding surfaces that separate them. The Neptune Gas Field lies on the northwest margin of the Southern North Sea gas basin and in Block 47/4b and extends into Blocks 47/5a and 42/29. Gas is reservoired in the Lower Leman Formation which in the Neptune Field, comprises a succession of stacked dry aeolian sandstones and thin, wet interdune deposits. Permeability varies significantly at the lamina and bedform scale and these variations impact the performance of production wells in the field. A deterministic reservoir simulation model was constructed prior to development drilling, with permeability determined from porosity–permeability transforms based on core analysis data. The collection of continuous bottom-hole pressure (BHP) data from three of the development wells showed that this model failed to match accurately the rate of pressure decline whilst flowing, and over-predicted the build-up pressure when the wells were shut in. Review of the sedimentological information revealed that heterogeneity in the aeolian sands was being lost in the modelling of permeability and the coarse upscaling. To test whether the poor dynamic history match was due to the deterministic model not incorporating the permeability heterogeneity, a fine-scale geocellular model was built to characterize the expected geological heterogeneity and then upscaled for flow simulation. To accommodate the range in scales of heterogeneity present, the modelling was undertaken in two principal steps. First, the lamina-scale effects were modelled to determine average flow properties perpendicular and parallel to dune migration directions. The results of the lamina-scale heterogeneity modelling were then incorporated into petrophysical models of dune bodies that were characterized by low permeability dune apron facies and high permeability base of dune slipface facies that grade upwards into moderate permeability slipface facies. Upscaling of the stochastic permeability grid captured the impact of the fine-scale heterogenetity and gave BHP responses at the development wells in better agreement with the production data than any deterministic permeability distribution modelled. The stochastic rock property distributions have, thus, been adopted as the base case in all future history match and reservoir performance prediction studies.

Modeling Three-Dimensional Groundwater Flow and Advective Contaminant Transport at a Heterogeneous Mountainous Site in Support of Remediation

Modeling Three-Dimensional Groundwater Flow and Advective Contaminant Transport at a Heterogeneous Mountainous Site in Support of Remediation Strategy Quanlin Zhou, Jens T. Birkholzer, Iraj Javandel, and Preston D. Jordan Ernest Orlando Lawrence Berkeley National Laboratory Earth Sciences Division 1 Cyclotron Road, MS 90-1116, Berkeley CA 94720 USA Abstract A calibrated groundwater flow model for a contaminated site can provide substantial information for assessing and improving hydraulic measures implemented for remediation. A three-dimensional transient groundwater flow model was developed for a contaminated mountainous site, at which interim corrective measures were initiated to limit further spreading of contaminants. This flow model accounts for complex geologic units that vary considerably in thickness, slope, and hydrogeologic properties, as well as large seasonal fluctuations of the groundwater table and flow rates. Other significant factors are local recharge from leaking underground storm drains and recharge from steep uphill areas. The zonation method was employed to account for the clustering of high and low hydraulic conductivities measured in a geologic unit. A composite model was used to represent the bulk effect of thin layers of relatively high hydraulic conductivity found within bedrock of otherwise low conductivity. The inverse simulator ITOUGH2 was used to calibrate the model for the distribution of rock properties. The model was initially calibrated using data collected between 1994 and 1996. To check the validity of the model, it was subsequently applied to predicting groundwater level fluctuation and groundwater flux between 1996 and 1998. Comparison of simulated and measured data demonstrated that the model is capable of predicting the complex flow reasonably well. Advective transport was approximated using pathways of particles originating from source areas of the plumes. The advective transport approximation was in good agreement with the trend of contaminant plumes observed over the years. The validated model was then refined to focus on a subsection of the large system. The refined model was subsequently used to assess the efficiency of hydraulic measures implemented for remediation.

Modeling Three‐Dimensional Groundwater Flow and Advective Contaminant Transport at a Heterogeneous Mountainous Site in Support of Remediation

A calibrated groundwater flow model for a contaminated site can provide substantial information for assessing and improving hydraulic measures implemented for remediation. We developed a three‐dimensional transient groundwater flow model for a contaminated mountainous site at which interim corrective measures were initiated to limit further spreading of contaminants. This flow model accounts for complex geologic units that vary considerably in thickness, slope, and hydrogeologic properties, as well as large seasonal fluctuations of the groundwater table and flow rates. Other significant factors are local recharge from leaking underground storm drains and recharge from steep uphill areas. The zonation method was employed to account for the clustering of high and low hydraulic conductivities measured in a geologic unit. A composite model was used to represent the bulk effect of thin layers of relatively high hydraulic conductivity found within bedrock of otherwise low conductivity. The inverse simulator iTOUGH2 was used to calibrate the model for the distribution of rock properties. The model was initially calibrated using data collected between 1994 and 1996. To check the validity of the model, it was subsequently applied to predicting groundwater level fluctuation and groundwater flux between 1996 and 1998. Comparison of simulated and measured data demonstrated that the model is capable of predicting the complex flow reasonably well. Advective transport was approximated using pathways of particles originating from source areas of the plumes. The advective transport approximation was in good agreement with the trend of contaminant plumes observed during the same years. The validated model was then refined to focus on a subsection of the large system. The refined model showed that most of the hydraulic measures implemented for remediation are effective.

Optimal elicitation of probabilistic information from experts

Abstract It is often desirable to describe information derived from the cumulative experience of human experts in a quantitative and probabilistic form. Pertinent examples include assessing the reliability of alternative models or methods of data analysis, estimating the reliability of data in cases where this cannot be measured, and estimating ranges and probable distributions of rock properties and architectures in complex geological settings. This paper presents a method to design an optimized process of elicitation (interrogation of experts for information) in real time, using all available information elicited previously to help in designing future elicitation trials. The method maximizes expected information during each trial using experimental design theory. We demonstrate this method in a simple experiment in which the conditional probability distribution or relative likelihood of a suite of nine possible 3-D models of fluvial-deltaic geologies was elicited from a geographically remote expert. Although a geological example is used, the method is general and can be applied in any situation in which estimates of expected probabilities of occurrence of a set of discrete models are desired.

Geostatistical characterization of the Carpinteria Field, California

This paper describes application of geostatistical techniques for detailed characterization of a geologically complex oil reservoir. The reservoir is mature and the characterization is aimed at facilitating its further development. A geological structure and stratigraphy model of the field has already been developed. Stochastic distributions of important reservoir rock properties were subsequently generated. Different techniques were applied to generate these distributions. A variety of data sources were integrated for each property. Multiple realizations were combined to assess uncertainty in property distributions. These measures of uncertainty and the detailed property realizations will be helpful for the field operator for assessing future field development scenarios.

Statistical Properties of the Bukit Timah Granite in Singapore

AbstractThe mechanical behavior of rock mass is affected strongly by its material properties. This paper carries out statistical analyses of the material properties of a rock mass. Statistical analyses of the material constants and the initial damage parameter of the rock mass are performed by using both field and laboratory test data. Based on the measured properties of rock specimens, the elastic modulus, uniaxial compressive strength, and the Poisson's ratio of rock are each found to have normal distributions and the tensile strength to have the gamma distribution. By using Monte Carlo simulation, the equivalent critical tensile strain is found to have the normal distribution. The initial damage of the rock mass, which describes the effects of naturally existing geological discontinuities in a rock mass, is estimated using the field-measured longitudinal and transverse elastic wave velocities. It is found to have the beta distribution. These distributions of rock properties can be used in statistical analyses of the rock mass responses to both static and dynamic loads.

Predicting oil recovery using percolation

One particular practical problem in oil recovery is to predict the time to breakthrough of a fluid injected in one well and the subsequent decay in the production rate of oil at another well. Because we only have a stochastic view of the distribution of rock properties we need to predict the uncertainty in the breakthrough time and post-breakthrough behaviour in order to calculate the economic risk. In this paper we use percolation theory to predict (i) the distribution of the chemical path (shortest path) between two points (representing well pairs) at a given Euclidean separation and present a scaling hypothesis for this distribution which is confirmed by numerical simulation, (ii) the distribution of breakthrough times which can be calculated algebraically rather than by very time consuming direct numerical simulation of large numbers of realisations.

Multiscale edge analysis of potential field data

Mapping the three-dimensional distribution of rock properties from potential field data is a difficult and arduous task, with inherent ambiguity remaining a major problem. We apply a combination of automated interpretation procedures, based on multiscale wavelet analysis and three- dimensional visualisation methods, in an attempt to extract geometrical information from potential field datasets, and display this information in an easily understandable and intuitive way. The resulting visualisations are similar to ‘worm’ maps commonly produced by interpretation of aeromagnetic data, but are defined in three dimensions.The techniques are tested on a series of synthetic and observed datasets, of varying complexity and geographical scale. The tests show both the effectiveness of the technique as an aid to the geological interpretation of potential field maps and in its use for providing constraints on the three-dimensional geology.The results of the testing on synthetic datasets show that for certain geometries there is an intuitive relationship between 3D edge location and shape, and subsurface geometries. Such relationships prove particularly robust even under ‘noisy’ conditions where surface features (e.g. the response of laterites in magnetic datasets) mask the coarser scale features that characterise the broader geological picture.Three real datasets at different geographical scales have been analysed. These include the Western Australian gravity dataset (representing the continent-scale), aeromagnetic data covering a 1:100,000 scale map sheet from central Victoria (representing the district-scale), and a prospect- scale aeromagnetic dataset from a mineralised greenstone terrane in Western Australia. The results produce different information at the different scales. At the continent-scale the multiscale edges allow discrimination of different tectonic styles, and comparison of the significance of crustal-scale structures. At the district- to prospect-scale, the edges can be used for geological mapping purposes such as to map subtle changes in sedimentary sequences, map alteration patterns, and constrain pluton geometries at depth.

Notes on the origin of formation fluid pressure: well-logging methods aspect

Current methods of pressure determination using well-log data are mostly based on porosity vs. pressure correlation and on the concept of pressure dependence on compaction processes due to overburden weight. However, natural compaction is a complex process, and many geologic and physical phenomena and processes other than compaction are known to generate pressure abnormalities. For these cases, pressure—porosity correlation may not be definitive, other parameters may correlate better, or no correlation may exist. For example in basins with no compaction or any other geologic activity, distribution of pressure deviations from hydrostatic pressure is solely determined by surface relief and by the 3-D distribution of water density and rock permeability. If a consolidated formation has fracture permeability and vertical fluid migration is a mechanism of abnormal pressure generation, usually no correlation exists between the vertical distribution of pressure and rock properties. All abnormal and subnormal pressure scenarios should be differentiated. Criteria to recognize each case and sets of parameters for indirect determination and/or prediction of formation pressure should be developed separately for each scenario. This will allow the maximum use of information pertinent to pressure distribution in each particular region or field and, therefore, more accurate pressure determination and prediction. In this paper, we formulate this problem and describe ways to develop new accurate methods of pressure determination using well-logs with other geologic information.

Crosswell seismic radial survey tomograms and the 3-D interpretation of a heavy oil steamflood

S‐wave, P‐wave, and Poisson’s ratio tomograms have been used to interpret the 3-D distribution of rock and fluid properties during an early phase of a California heavy oil sand steamflood. Four lines of good quality crosswell seismic data, with source to receiver offsets ranging from 287 to 551 ft (87 to 168 m), were acquired in a radial pattern around a high temperature cemented receiver cable in four days. Processing, first‐arrival picking, and good quality tomographic reconstructions were completed despite offset‐related variations in data quality between the long and short lines. Interpretation was based on correlations with reservoir models, log, core, temperature, and steam injection data. S‐wave tomograms define the 3-D distribution of the “high flow” turbidite channel facies, the “moderate‐low flow” levee facies, porosity, and structural dip. The S‐wave tomograms also define an area with anomalously low S‐wave velocity, which correlates with low shear log velocities and suggests that pressure‐related dilation and compaction may be imageable. P‐wave tomograms define the same reservoir lithology and structure as the S‐wave tomograms and the 3-D distribution of low compressional velocity zones formed by previous steam‐heat injection and the formation of gas. The low P‐wave velocity zones, which are laterally continuous in the “high flow” channel facies near the top of most zones, indicate that the steam‐heat‐gas distribution is controlled by stratification. The stratigraphic control of gas‐bearing zones inferred from P‐wave tomograms is confirmed by Poisson’s ratio tomograms which display low Poisson’s ratios indicative of gas (&lt;0.35) in the same zones as the low P‐wave velocities. The interpretation results indicate that radial survey tomograms can be tied at a central well and used to develop an integrated 3-D geoscience‐engineering reservoir model despite offset‐related variations in data quality. The laterally continuous, stratification‐controlled, low P‐wave velocity zones, which extend up‐dip, suggest that significant amounts of steam‐heat are not heating the surrounding reservoir volume but are flowing updip along “high flow” channels.

Tertiary Recovery Modeling By Hybrid Simulation For Kaybob Beaverhill Lake 'A' Pool Hydrocarbon Miscible Flood

Abstract A Hybrid finite-difference/stream tube simulation was run for Kaybob BHL ‘A’ HCMF to identify optimization opportunities and provide an accurate forecast. Five different cross-sections were chosen to represent the different geologic regions of the Kaybob reef. Detailed 2-D simulation models were built and run with many operating variations. The 2-D cross-section results were mapped onto a field-wide stream tube model giving 3-D results for each pattern under a variety of operating conditions. The model was restricted to tertiary oil only and an excellent match was found with field data. The accuracy of the simulation without history matching shows the modeling benefits of incorporating: (1) detailed rock property distributions in a cross-section to model channeling and override mechanisms, (2) geologic diversity, and (3) off-pattern migration and variations in areal sweep efficiency unique to each pattern. Introduction Background of Pool Kaybob Beaverhill Lake ‘A’ Pool is a carbonate reef with multiple growth stages. Original oil in place is estimated at 40.3 106m3 covering approximately 7,700 ha. The pool produced 5% OOIP under primary depletion between discovery in 1957 and start of line drive water injection in January 1964. From 1964 to 1973 the number of injectors expanded slowly from four to eight: recovery increased to 26%. The waterflood was converted to pattern injection in 1978, which expanded to 15 injectors by the start of miscible flood in July 1988. Well rates changed greatly during the waterflood with different wells being on injection and producers often shut in upon initial water production in the early days. Recovery was 15.8 106m3 or 39% prior to solvent injection. Waterflood production in Kaybob has been extremely good with ultimate recovery expected at 18.7 106m3 or 46.5%. The waterflood benefits from the unusually high viscosity ratio of µw/ µo= 2.5. A hydrocarbon miscible flood (HCMF) was chosen for tertiary recovery. Phase 1, containing eight patterns of the horizontal drive miscible flood, started in July 1988. Phase 2, with eight more patterns, started in March 1989. Phase 3 has not yet been implemented as originally planned. The initial design has been described previously(1,2). Objectives of Hybrid Simulation Study Previous studies were not able to address several outstanding concerns for miscible flood operation because they did not include the necessary level of detail. Two years after solvent injection started, this simulation project was started. This study had three primary objectives:optimization of individual patternssolvent slug size and WAG ratio chase fluid designforecasts for economic justificationswell workovers and stimulationssurface facilitiesflood expansionbusiness plan and marketing forecastsoil productionsolvent injection and production FIGURE 1: Hybrid model uses results from a 2-D finite-difference cross-section model mapped unto a 2-D streamtube areal model. (Available in full paper) Background of Hybrid Simulation Method The concept of combining a finite-difference simulation of a vertical cross-section with an areal streamtube simulation was first reported in 1981(3). This method was used to reduce the finite-difference simulation to a manageable size for a surfactant/polymer flood.