Truncated Gaussian Simulation Research Articles

Carbonate reservoir characterization and permeability modeling using Machine Learning ـــ a study from Ras Fanar field, Gulf of Suez, Egypt

AbstractPredicting facies and petrophysical properties along and between wells is challenging in carbonate reservoir modeling. In the Nullipore carbonate reservoir, Ras Fanar field, depositional and long-term diagenetic processes result in a high degree of heterogeneity and complex distribution of facies, which in turn affect the reservoir quality. This provides a significant obstacle to building accurate geological models. This study integrates thin sections, routine core analyses, and well logging data to overcome such difficulties and model the Nullipore carbonate facies and permeability. The detailed petrographic analysis revealed the existence of seven microfacies in the reservoir, which are summed up into three facies associations (FAs), each of which represents a specific reservoir rock type (RRT): (1) supratidal FA, (2) intertidal FA, and (3) shallow subtidal FA. The three FAs were correlated with the gamma-ray logs to create facies logs for the studied wells, which were further populated via the Truncated Gaussian Simulation method. Cross-validation was used to evaluate the model's accuracy. The analysis of the available core data infers that the three RRTs are prospective and have a wide permeability distribution. However, RRT3 constitutes the best reservoir quality. The sedimentological analysis revealed that the long-term diagenetic events, involving the dolomitization of limestone and the dissolution of allochems have a major role in improving the pore connectivity and permeability of the reservoir. Fracture characterization discloses that fractures play a significant role in fluid storage and migration. Three Machine Learning (ML) models, including Adaptive boosting (AdaBoost), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB), were developed to integrate the RRTs, porosity, and permeability to improve permeability prediction. Statistical analysis revealed that the XGB model outperforms other models and exhibits the highest prediction performance. The present study provides further insights into the characterization and modeling of facies and permeability of complex carbonate reservoirs. It can be applied in similar geological settings to better interpretation of depositional and diagenetic controls on reservoir quality assessment and aid in the field development plan.

Specification and formation process of enriched portions in Au veins in an epithermal deposit via clustering and geostatistical approaches

Even though epithermal vein-type deposits are the main sources of Au and Ag worldwide, accurate three-dimensional modeling of vein structures and the extraction of high-grade zones are still difficult because of geologic structure heterogeneities and the scarcity of available data, mostly obtained via drilling. Accordingly, by selecting a low-sulfidation epithermal Au–Ag deposit in the Philippine archipelago, we develop an efficient and reliable workflow for determining the spatial distribution of Au-rich veins in detail and the transport of hydrothermal fluids. The studied deposit is mostly hosted in open fractures and breccias with a relatively large tonnage of low Au+Ag grades and/or a small tonnage of high Au+Ag grades. The whole-rock geochemical data (1877 core samples) and lithological data (56 drilling sites) are processed using hierarchical clustering analysis (HCA) and two geostatistical simulations: turning bands simulation for the Au grade distribution and interpretation of mineralization process and truncated Gaussian simulation for the spatial distribution of clusters with similar Au–Ag grade features as classified by HCA. The general correlation between the Au and Ag grades, with a linear correlation coefficient of ≈ 0.69, is based on the HCA application, and the clusters were likely formed by three-stage mineralization processes. A plausible three-dimensional geologic model is then constructed, delineating in detail hydrothermally mineralized and altered zones with Au enrichment and vein system structures in the study area.

Lithofacies and electrofacies models for Mishrif Formation in West Qurna oilfield, Southern Iraq by deterministic and stochastic methods (comparison and analyzing)

In this study, the researchers attempted to build models that are more accurate by using lithofacies data along the field. Using a wider field area and extended data from both electrofacies and lithofacies could provide an accurate model of the reservoir description that will be useful for future field developments. The stochastic and deterministic models were presented to build the facies model as the basis for the construction, comparison, and selection of the more accurate model of the Mishrif Formation in the West Qurna oilfield/Iraq. The results obtained from this study indicated that the Sequential Gaussian indicator simulation algorithm offered a more accurate stochastic model between lithofacies data extracted from 20 wells and electrofacies from 75 wells, while the Truncated Gaussian simulation algorithm has a better match than others for the distribution percentage of lithofacies and electrofacies. The stochastic model shows that Mishrif Formation consists of approximately 35–40% as carbonates, 32–35% as shale, and 28–30% as coarse sand, Dolomite, and other materials according to the SISIM and GTSIM, while the deterministic by the kriging algorithm referred to as 62%, 24%, and 14%, respectively. The best variogram that gives the best results indicated that the direction of facies distribution is mainly South-North with an inclination to North-West.

Multiple trend integration method based on depositional model and its application in glutenite reservoir modeling

Strong heterogeneity, complicated lithology, and chaotic seismic reflection characteristics are all common features of glutenite reservoirs. It is challenging to pinpoint the interior lithology and quantitatively describe the heterogeneity of the single-stage glutenite. To explore the distribution and superimposition features of subaqueous fans, the upper Es4 in the Y229 region of Dongying sag was used as an example. We have developed a multitrend fusion constraint modeling method based on deposition patterns. First, the truncated Gaussian simulation method is used to establish the sedimentary subfacies model of the subaqueous fan. Second, one lithologic probability volume is generated according to the proportion of various lithology of different sedimentary subfacies. Then, the lobes model is constructed using the object-based simulation method and the quantitative parameters from outcrop and flume sedimentation simulations. In addition, a different lithology probability volume is determined based on how far a particular lobe is from the centerline. The two probability volumes are combined to create the integrated lithology probability volume, which reflects the planar trend and the internal differences of different lobes. To constrain lithologic modeling, the integrated lithology probability volume is used. By comparing the model results with a single-trend constraint, the findings indicate that the multitrend integration constraint modeling method may more accurately depict the internal variability of the glutenite reservoir. In addition, the lithologic model built on this foundation is consistent with the depositional model.

3D Quantitative Prediction of the Groundwater Potential Area-A Case Study of a Simple Geological Structure Aquifer.

The Ordos Basin is a sedimentary basin located in Inner Mongolia, China, where coal and uranium coexist. Water inrush disasters have always been one of the main disasters that threaten the safety of coal mine production, and thus, the study and division of groundwater potential regions are of great significance for the prevention of water inrush disasters and in situ leaching of sandstone-type uranium ore. A new method combining truncated Gaussian simulation and sedimentary facies control was established to predict the groundwater potential area. Taking a typical aquifer, the Zhiluo Formation, as an example, based on high-resolution sequence stratigraphy, geophysics, sedimentary geology, and geostatistical theory, the plane distribution of sand bodies was predicted. Furthermore, the relationship between rock porosity and electricity porosity was established to calculate the regional porosity. Combined with truncated Gaussian simulation and facies-controlled modeling methods, a facies-controlled heterogeneous property model was established to analyze the heterogeneous effective porosity of the aquifer in the study area. Groundwater potential areas were quantitatively evaluated by 3D modeling analysis. The results of the evaluated model were verified by actual data and provide a geological guarantee for the accurate mining of deep coal and uranium ore. A 3D distributed model of chemical elements, which is meaningful for in situ leaching uranium mining, is expected in future research.

Feature-based ensemble history matching in a fractured carbonate reservoir using time-lapse deep electromagnetic tomography

Carbonate reservoirs typically exhibit very complex geological structures and are characterized by flow dynamics primarily occurring in fractures. The intricate network of fractures as well as their interconnectedness may lead to unexpected flow patterns and uneven sweep efficiency. Determining reservoir properties of both matrix and fracture channels is quintessential for accurately tracking the fluid front movement in the reservoir, optimizing sweep efficiency, and maximizing hydrocarbon production. In this study, we showcase the application of a feature-oriented ensemble-based history matching workflow to a complex fractured carbonate reservoir box model, focusing on the use of formation resistivity tomography data that are usually inferred from deep crosswell electromagnetic (EM) surveys. Compared with the production data that are commonly used in history matching, deep EM measurements provide additional information about the spatial distribution of subsurface reservoir properties in the interwell volumes by exploiting the strong resistivity contrast between water and hydrocarbons. A hybrid parameterization approach is used to represent the multiscale fracture distribution in which the spatial distribution of small-scale fractures is modelled by a truncated Gaussian simulation method. A large number (over one million) of uncertain model parameters including reservoir matrix and fracture properties as well as Archie's parameters are identified and updated by an iterative ensemble smoother. For an efficient integration of the high-dimensional and noisy EM tomography data, the boundary or contour information extracted from the EM resistivity field is instead assimilated through a distance parameterization approach. A modified bootstrap-based localization is proposed to regularize the model updates adaptively during the iteration to reduce sampling errors. Especially, to improve the computational efficiency in dealing with the large dimensions of both data and model parameters, the localization is implemented in a projected low-dimensional data subspace. Experimental results demonstrate the applicability and efficiency of the developed workflow for reservoir history matching in more realistic model settings. The comparative case study also illustrates the significance of jointly incorporating multiple sources of data for better quantification of model uncertainty, and the great potential of deep EM data for enhancing the characterization of complex fractured carbonate reservoirs.

The Lithofacies Classification and Its Influence on the Gas Production Capacity in the Shale Gas Production Area

The gas production capacity difference among single wells and the difficulties in sustaining stable production are the key problems faced by shale gas production areas. Based on the typical characteristics of the shale gas production areas， a technical process for the lithofacies classification of high-quality marine shale affected by the gas production capacity was established in this paper. Firstly， for the high-quality marine shale in the shale gas production area， the main gas production capacity difference control factors were analyzed， and the lithofacies classification scheme was determined. Then， using the developed logging calculation model of total organic carbon （TOC） content， porosity， clay， siliceous， and calcareous mineral content， the single well parameter calculation and the lithofacies identification in one shale gas producing area were completed. A total of 10 types of shale lithofacies were identified in one shale gas production area， and the relationship between shale lithofacies type and gas production capacity difference was revealed by comparing the gas content of each lithofacies. Finally， a three-dimensional （3D） lithofacies model in one shale gas production area was established by using the truncated Gaussian simulation algorithm and the sedimentary microfacies confined lithofacies strategies， the spatial distribution characteristics of each kind of lithofacies were shown， and the gas production capacity difference in the Wufeng-Longmaxi black shale in the study area was revealed. At the same time， according to the two conditions of large volume proportion and great gas potential in 3D space， the three different lithofacies with excellent gas production capacity in the study area were determined as i. rich in carbon， high in porosity， calcium， muddy siliceous shale， ii. rich in both carbon and porosity mixed shale， and iii. high in carbon， medium to high in porosity， calcium， muddy siliceous shale. The above results are helpful for explaining the essential causes for the great difference in the decline amplitude and output effect of shale gas production areas， laying a solid theory foundation and technical support for fine production management in shale gas production areas.

Connectivity in Pixel-Based Facies Models

This study investigates whether pixel-based geostatistical modelling methods can be used to generate high net:gross ratio models with low connectivity of the net facies, a common combination in many natural geological systems. Connectivity as a function of net:gross is systematically measured in stationary, representative, horizontally isotropic three-dimensional models generated using three different pixel-based geostatistical methods: sequential indicator simulation, truncated Gaussian simulation and multiple-point statistics modelling. All methods are found to have percolation thresholds similar to, or substantially lower than, that of a random object-based model in which the net facies becomes macroscopically connected at a critical net:gross ratio of 0.27. A geometrical transformation previously defined for object-based models known as the compression method has been adapted to deal also with pixel-based models. Application of the method, calibrated using the newly established percolation thresholds, allows construction of geologically realistic facies models using a range of pixel-based methods. The resultant models contain quantifiable levels of connectivity that are defined independently of the model net:gross ratio.

Geological process modeling and geostatistics for facies reconstruction of presalt carbonates

The presalt reservoirs of the Barra Velha Formation are complex and heterogeneous. Their deposition was controlled by a mixture of physical and chemical processes, which consequently affected the distributions of facies and variations in porosity and permeability. In this paper we present a presalt facies reconstruction of reservoirs within the Barra Velha Formation of the Búzios Field. This was achieved through the use of an innovative workflow that integrates geological process modeling with a truncated Gaussian simulation geostatistical algorithm with trends. Our results show that the structural highs are dominated by carbonate build-ups/mounds architecture seismic patterns which are dominated by spherulites and its intercalation with shrub sediments culminating in spherulitites and shrubby carbonate lithologies. Reworked sediments and facies are concentrated in regions dominated by debris seismic patterns and lake bottom seismic facies corresponding to laminites also occur within the study area. In chronostratigraphic terms the Barra Velha is muddier at the base transitioning to in-situ carbonates in the middle section, before becoming muddier again at the top. The western portion of the Búzios Field is mostly composed by shrubby carbonates and reworked facies whilst spherulitities are more abundant to the east intercalated with shrubby carbonates. Some uncertainties remain in relation to the parameters used in the proposed methodology. Nonetheless, the proposed workflow was effective for facies reconstruction of the presalt carbonates allowing not only a better understanding of sedimentological processes but also accurately distributing facies throughout the study area.

Facies modeling of synchronous successions - A case study from the mid-cretaceous of NW Zagros, Iran

Facies modeling of Albian-Turonian successions at Tang-e-Bijar gas field in the Lurestan Province, NW of the Zagros region, Iran is the main objective of this study. The sedimentary environment and biozones of the Sarvak and Garau formations (Albian-Turonian time) are different in Lurestan Province when compared with the south Zagros and the Persian Gulf ranges. Synchronous successions of the formations with different lithofacies and laterally changing of biofacies are always controversial. The primary objectives of this paper is to determine the concurrency of the Sarvak and Garau successions using the correlation of foraminifera biozones and subsequent modeling of simultaneous lithofacies via employing the Truncated Gaussian Simulation with a trend (TGSim) algorithm. In this regard, the Tang-e-Bijar and nearby field data such as core data and petrophysical logs, paleontological and stratigraphy studies were taken into consideration. The stratigraphic ranges of the two formations were determined as Albian-Turonian age. Based on these biostratigraphic data, the tongue of the Garau Formation was clarified. The sequence stratigraphy zonation has been used for the entire Tang-e-Bijar field wells, based on Integrated Prediction Error Filter Analysis (INPEFA) logs and core data. In order to capture the heterogeneity of deep sea lithofacies, MRGC clustering method with supervising lithofacies was implemented in this study and five electrofacies were generated and coded from 1 to 5. They correspond to Rudist-Oncoids, packstone to grainstone (RO), Orbitolinid peloid packstone (OP), Fine Orbitolinid wackestone to packstone (FO), Bioturbated echinoderm mudstone to wackestone (BM), and Oligosteginid Mudstone (OM) lithofacies, respectively. The facies modeling in the reservoir such as Tang-e-Bijar where synchronous successions and laterally transient heterogeneous has occurred has always been challenging. To address this challenge, a new workflow has been implemented in this paper.

Discrete-NTG Truncated Gaussian Simulation: An Alternative Modeling Approach for Coal-Seam-Gas Unconventional Reservoirs, Bowen Basin, Eastern Australia

Summary Building a representative static model for predicting and monitoring the performance of coal-seam gas (CSG) fields presents several complex and unique challenges. The individual reservoirs possess different coal architectures, often with highly complex seam splitting, amalgamating, and structural deformation. Our objective was to develop an alternative approach that honored log and core data capturing both the lateral heterogeneity and the vertical signature of the Bowen Basin coals in Central Queensland. In some areas of the Bowen Basin, coals can be thick and laterally continuous; picking the top and base of each seam works well in small models with homogeneous coals. As seam geometries begin to increase in complexity and coals become more heterogeneous in nature with thinner seams in multiple packages, then a net-to-gross (NTG) approach is often more appropriate. Each method has its merits. The former approach describes the reservoir architecture but implies a certain degree of confidence in coal correlation. In a vast field with complex seam splitting and merging with abundant drilling data, it might not be a practical technique. The NTG method disregards coal-seam architecture and reservoir connectivity. The proposed workflow is a hybrid approach using discrete modeling algorithms and data-analysis tools on continuous NTG properties. The process operates on a relatively coarse chronostratigraphic framework in which coal is captured as contiguous discrete-NTG “facies.” The use of the truncated Gaussian model ensures the ordering of NTG facies and mimics transitions between coals and the surrounding interburdens. With the adoption of facies vertical proportion trends, we are able to replicate a similar coal-seam signature laterally away from the wellbore. The definition of a categorical coal model allows the proper scaling of seams with different coal-quality characteristics. With the successful geocellular-model construction and history match of two historical CSG fields in the Bowen Basin, the discrete-NTG truncated Gaussian simulation (TGS) approach has proved to be a valid alternative CSG-modeling technique.

High-resolution geostatistical modeling of an intensively drilled heavy oil reservoir, the BQ 10 block, Biyang Sag, Nanxiang Basin, China

Abstract Establishing a high-resolution subsurface model is the ultimate goal of reservoir characterization. The “BQ 10 Block”, in Biyang Sag of Nanxiang Basin in China, is a data-rich mature field with heavy oil deposits penetrated by over two hundred wells with an average well spacing of 75m. The aim of this study is to establish a three-dimensional high-resolution model of the BQ 10 reservoir and to accurately and efficiently derive its geological and geometrical properties. A geostatistical modeling study was carried out in combination with stratigraphic correlation, core observations, log interpretation, lithology estimation, and sedimentary facies analysis. Based on core and wireline log data, lithology and conventional well logs (i.e. resistivity, gamma ray, and spontaneous potential) were correlated first. Lithofacies data at cored well locations were grouped into petrofacies units based on reservoir quality data. Using a neural network method, petrofacies at uncored wells was predicted based on correlation with conventional well logs. For different petrofacies, statistical analyses revealed correlation between laboratory porosity and permeability with acoustic well logs. A petrofacies model was built alternatively with indicator kriging, truncated Gaussian simulation (TGS), and sequential indicator simulation (SIS). SIS with a 3D trend model was identified to give the most reasonable petrofacies distribution. Using this model, facies-controlled petrophysical property modeling was performed using sequential Gaussian simulation (SGS). A validation procedure based on “minimum acceptance criteria” was employed to ensure that the SIS/SGS realizations are consistent. For this data-rich reservoir, this study demonstrates an effective application of the standard geostatistical modeling techniques on constructing high-resolution reservoir models of a heavy oil reservoir. The final suite of models reveal a likely range of reservoir facies and petrophysical property distributions for BQ 10, which can be useful for designing heavy oil recovery operations.

An approach for three-dimensional quantitative carbonate reservoir characterization in the Pampo field, Campos Basin, offshore Brazil

In carbonate rock reservoirs, spatial distribution models and elastic properties are complex because of diagenetic processes and mineralogical composition, which together directly interfere with variations in pore shape and interconnectivity. The main objective of this paper is to propose a workflow to aid in three-dimensional quantitative carbonate reservoir characterization of the Quissama Formation (Macae Group) in the Pampo field of the Campos Basin, offshore Brazil. Model-based seismic inversion, sequential Gaussian simulation with cokriging for porosity modeling, and truncated Gaussian simulation with trend for facies modeling were used to characterize the carbonate reservoirs. Our results show that the carbonate platform is located between the upper Aptian and lower Albian seismic surfaces. Interpretation of a new surface, called the intra-Albian, was possible via acoustic-impedance (AI) analysis. Our workflow facilitated identification of low AI, high porosity, and best facies areas in structural highs where the most productive wells have been drilled. Facies modeling suggests that intercalation of facies with high and low porosities is connected to shallowing-upward cycles. Finally, several debris facies with low AI and high porosities were identified in an area that could be targeted for new exploration.

New Tabu Algorithm for Positioning Mining Drillholes with Blocks Uncertainty

This paper proposes a new approach to the mining exploration drillholes positioning problem (DPP) that incorporates both geostatistical and optimization techniques. A metaheuristic was developed to solve the DPP taking into account an uncertainty index that quantifies the reliability of the current interpretation of the mineral deposit. The uncertainty index was calculated from multiple deposit realizations obtained by truncated Gaussian simulations conditional to the available drillholes samplings. A linear programming model was defined to select the subset of future drillholes that maximizes coverage of the uncertainty. A Tabu Search algorithm was developed to solve large instances of this set partitioning problem. The proposed Tabu Search algorithm is shown to provide good quality solutions approaching 95% of the optimal solution in a reasonable computing time, allowing close to optimal coverage of uncertainty for a fixed investment in drilling.

A Semi-Analytical Method for History Matching and Improving Geological Models of Layered Reservoirs: CGM Analytical Method

History matching is used to constrain flow simulations and reduce uncertainty in forecasts. In this work, we revisited some fundamental engineering tools for predicting waterflooding behavior to better understand the flaws in our simulation and thus find some models which are more accurate with better matching. The Craig-Geffen-Morse (CGM) analytical method was used to predict recovery performance calculations and it was simple enough which can be applied in a spreadsheet. In this study, the analytical approach of history matching was applied to a layered reservoir from a shallow marine deposit which was composed of different facies includes lower shoreface facies (LSF), middle shoreface facies (MSF) and upper shoreface facies (USF). Truncated Gaussian Simulation (TGS) is often used to stochastically distribute the facies in the geological model around a deterministic mean representation. The actual distribution is often hard to determine. Starting with the deterministic element of the facies distributions, corrections were made by matching the CGM method predictions to historical data. These corrections were amalgamated in the model and produced a much better history match. Further, the modifications were used to condition the stochastic simulator to provide a geologically more robust model that also matched history. The results showed that the variation of the total field production rate (FPR) between the deterministic model and history data was reduced by about 19.8% (from 21.52% to 1.73%) after applying history match analytically.

FACIES HETEROGENEITIES IN A RAMP CARBONATE RESERVOIR ANALOGUE: A NEW HIGH‐RESOLUTION APPROACH FOR 3D FACIES MODELLING

In contrast to the conventional view that facies distribution patterns on carbonate ramps are relatively simple, outcrop analogue studies point to a high degree of internal facies complexity. Depending on the diagenetic overprint, this complex pattern may result in reservoir compartmentalization due to the presence of interflow baffles. The often subseismic scale heterogeneities may not be included in conventional reservoir modelling. In order to evaluate how facies heterogeneities in shoal reservoirs can be modelled realistically, this paper presents a facies modelling workflow which includes a new approach to the design of training images for multiple‐point statistics (MPS). The workflow was developed in the course of a reservoir outcrop analogue study of a Ladinian (Middle Triassic) coquinadominated shoal complex in SW Germany which was deposited on an epicontinental, gently inclined carbonate ramp. The data set was based on an intensive field study and includes 3D facies and sequence stratigraphic analyses of the largest shoal complex in the Quaderkalk Formation (Upper Muschelkalk). This several metre thick shoal complex represents a subseismic scale, bioclast‐rich reservoir analogue and has a very heterogeneous facies pattern.Integrating 1D facies logs and sequence stratigraphic trends from tens of outcrop sections and cores, two nested 3D geocellular facies models were produced: (i) a large‐scale (30 × 30 km) model based on truncated Gaussian simulation (TGS); this formed the basis for (ii) a smaller‐scale (10 × 10 km), more detailed model based on multiple point statistics. In addition, a new approach for training image design was developed to honour small‐scale sequence stratigraphic trends and lateral facies patterns observed in modern analogues. Compared to facies patterns in modern analogues, the large‐scale model presents geologically‐feasible facies distribution patterns and geometries, and in addition shows a vertical facies distribution which is similar to the observed sequence stratigraphic architecture of the outcrop data‐set used. Due to the new training image design, the final small‐scale model has a distribution pattern of facies heterogeneities which looks similar to modern facies distributions in the offshore UAE and thus represents a valuable method of producing realistic reservoir facies models.The modelling workflow and the new approach for training image design presented will help to reduce uncertainties in the understanding and modelling of subsurface reservoirs by using a systematic combination of outcrop data and modern analogues, with the consistent application of sequence stratigraphic principles. In addition, this study emphasises the importance of careful training image design, derived from modern analogues, which can be used as realistic inputs in order to optimize multiple point simulations, and which may be applied to producing bioclastic reservoirs such as those located on the Arabian Plate or offshore Brazil.

Geostatistical facies modeling trends for oolitic tidal sand shoals

To assess prospective modeling trends for oolitic tidal sand shoals and explore potential patterns of reservoir heterogeneity, this study examines, quantifies, and models the cycle-scale architecture of the Holocene mobile oolitic tidal sand shoal complex at Schooner Cays, Bahamas. Process-based stratigraphic trends are captured in quantitative, geocellular models of the shoal from analyses of satellite imagery; two-dimensional, high-frequency seismic (chirp) data; and sediment cores. Data show that longitudinal tidal sand ridges extend up to 8 km (5 mi) along depositional dip, gradually transforming bankward into channel-bound, compound barforms consisting of linear, parabolic, and shoulder bars. These bars terminate into a laterally extensive (10 km [6 mi]), strike-elongate sand sheet. Each bar type includes distinct internal architecture, grain size, and sorting related to feedbacks among hydrodynamics, geomorphology, and sedimentology. Building on these data and concepts from the Holocene accumulations, this study demonstrates a methodology for quantifying and validating probabilistic stratigraphic trends prior to their inclusion in stochastic-based facies modeling algorithms. Inclusion of statistically robust facies probability volumes during truncated Gaussian simulation generated ordered and geologically accurate facies distributions relative to bar-crest centerlines, water depth, and geomorphic position. Petrophysical models that incorporate facies-specific porosity, permeability, and water saturation functions display pronounced cycle-scale heterogeneity that could provide insights into variable production rates and poor sweep efficiency commonly encountered during development of analogous oolitic reservoirs.

Application of truncated gaussian simulation to ore-waste boundary modeling of Golgohar iron deposit

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple and informative example of such a boundary, one can consider the boundary between ore and waste materials in an ore deposit. This boundary addresses the percentages of the ore and the waste, and also affect the future economy of mine and all precedent mine designs and mine plans. Deterministic approaches, based on interpretation of geological phenomenon, provide just one scenario of ore-waste variation, and do not offer a model for uncertainty of boundaries. On the other hand, geostatistical simulations, based on stochastic models, can measure the uncertainty of such a boundary. Through different techniques for spatial simulation of the categorical data (geological domains) truncated gaussian simulation has been proved to be versatile when geological units have sequential geometries and/or there are few number of indicators (ore and waste). This study addresses the application of TGS for conditional simulation of ore and waste domains in Golgohar iron ore deposit. Separation of the ore and waste domains has affected the ore tonnage estimation and resource evaluation. Various simulations can be considered as the spatial realizations of ore and waste. TGS can generate realizations of the domains and measure the uncertainty of ore-waste boundary. The accuracy of result has been checked through performance evaluation section and different scenarios (e.g. best, average and worst). The best scenario is the one with the most accuracy that is calculated from confusion matrix. The scenario No. 44 with 96 million cubic meters tonnage has an accuracy over 86 percent that is proposed as the best scenario for future mine design and planning.

Facies architectural analysis and three-dimensional modeling of Wen79 fault block, Wenliu oilfield, Dongpu depression, China

Wenliu oilfield is one of those typically structural reservoirs in Dongpu depression in China. Wen79 fault block is located in the south of Wenliu oilfield. Nowadays, it has entered the secondary oil recovery stage with a high water cut. Accumulated repository from long-term exploration and production makes the opportunity to fulfill a fine description of Wen79 fault block optimistic. Eight basic lithofacies types (Gt, St, Sp, Sl, Sh, Sr, Fl, Fm) were identified through core observation, and brief description and interpretation were given to each lithofacies. Assemblages of associated facies were arranged into four specified architectural elements (channel fill, proximal overbank, distal overbank, and shallow lake). For the purpose of quantified reservoir physical property characterization, a three-dimensional (3-D) architectural element model was firstly constructed by using the stochastic reservoir modeling technique, truncated Gaussian simulation (TGS). Subsequently, we used the sequential Gaussian simulation (SGS) method to capture probable distributions of reservoir porosity and permeability with the help of facies-controlled method. Meanwhile, non-facies-controlled physical property models were also built for a comparative study. Analysis of both kinds of models indicates that the facies-controlled physical property model is more reliable.

Quantifying the uncertainty in the spatial layout of rock type domains in an iron ore deposit

This work addresses the problem of delineating the spatial layout of ten rock type domains in an iron ore body and of assessing the uncertainty in the domain boundaries. A stochastic approach is proposed to this end, based on truncated Gaussian simulation, which consists in defining successive partitions of the space that comply with the desired spatial continuity and contact relationships between rock type domains. The sequencing of these domains is driven by their position (surficial vs. underlying rocks), granulometry (compact vs. friable rocks), and grades (rich vs. poor) of iron, alumina, manganese and loss on ignition. A total of 100 realizations are produced, conditioned to available drill hole data, and used to quantify the uncertainty in the occurrence of each rock type domain, at both global and local scales.