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The incorporation of hard data in geostatistical modeling is crucial for enhancing the accuracy of interpolating or stochastically estimating subsurface spatial features. The hard data at specified points in the model domain serve as a guide in optimizing the unknown parameters to follow the patterns of the hard data. Recently, a novel approach to solving hydrogeologic/reservoir modeling problems has emerged by using deep generative models, specifically generative adversarial networks (GANs), to generate realistic and diverse images of channelized aquifers. This subsequently can be coupled with inverse models to solve parameter estimation problems. This study focused on using an improved GAN, called a progressive growing generative adversarial network (PGGAN), conditioned with hard data to perform parameter estimation of complex facies models by coupling an ensemble smoother with multiple data assimilation (ES-MDA). First, the PGGAN was trained to an image with 128 × 128 resolution. The trained PGGAN was used to generate hydraulic conductivity fields when fed an ensemble of latent variables and hard data. The ES-MDA then was used to update the latent variable with the help of hydraulic head data obtained from the groundwater model. The approach was tested on synthetic hydraulic conductivity data. Results show that this approach was able to perform efficient estimation of an unknown facies model domain. Additionally, the proposed method was applied to a different test case of a facies model exhibiting different statistical characteristics. The results were satisfactory, demonstrating that the method is not constrained to the particular hydraulic conductivity fields introduced in the generator's training. • Coupling deep learning with data assimilation for groundwater modeling. • Both hard data and soft data are conditioned. • Synthetic examples are used to demonstrate the effectiveness. [ABSTRACT FROM AUTHOR]

New geophysical data from the leeward slope of Great Bahama Bank show how contour currents shape the slope and induce re-sedimentation processes. Along slope segments with high current control, drift migration and current winnowing at the toe of slope form a deep moat. Here, the slope progradation is inhibited by large channel incisions and the accumulation of large mass transport complexes, triggered by current winnowing. In areas where the slope is bathed by weaker currents, the accumulation of mass transport complexes and channel incision is rather controlled by the position of the sea level. Large slope failures were triggered during the Mid-Pleistocene transition and Mid-Brunhes event, both periods characterized by changes in the cyclicity or the amplitude of sea-level fluctuations. Within the seismic stratigraphic framework of third order sequences, four sequences of higher order were identified in the succession of the upper Pleistocene. These higher order sequences also show clear differences in function of the slope exposure to contour currents. Two stochastic models emphasize the role of the contour currents and slope morphology in the facies distribution in the upper Pleistocene sequences. In areas of high current influence the interplay of erosional and depositional processes form a complex facies pattern with downslope and along strike facies alterations. In zones with lower current influence, major facies alternations occur predominately in downslope direction, and a layer-cake pattern characterizes the along strike direction. Therefore, this study highlights that contour currents are an underestimated driver for the sediment distribution and architecture of carbonate slopes. [ABSTRACT FROM AUTHOR]

This study includes a new understanding of the depositional model of Abu Roash “C” Member deposited in Sitra Field in Abu Gharadig Basin during Turonian time, and illustrates the major affecting factors that control the behavior of this reservoir and consequently offer a great opportunity for Sitra field’s future development activities through a new methodology to maximize the field’s ultimate recovery. The Sitra development lease is located in north Western Desert and occupies the central western part of Abu Gharadig Basin and covers the southern extension of Badr El-din Petroleum Company (BAPETCO) leases with an area of 322.4 km 2 . Sitra Area is divided into several structural closures; the main producing one is the Sitra 8 block in which 39 wells were drilled since 1993. Various data from these wells were evaluated to construct the depositional facies models for the Abu Roash “C” reservoir. The log analyses have been integrated with the core descriptions, and ditch cutting data to interpret the depositional facies model that controlled the reservoir characteristics. In Sitra Area the Abu Roash “C” Member exhibits all of the characteristics of the Shallow Marine-Tidal dominated estuaries which are linked to the south with a fluvio-marine environment, the tide-dominated estuaries are represented in tidal channels and tidal flat facies, march deposits, and distributary mouth bars. The best reservoir rock in the Abu Roash “C” Member was deposited as distributary channel fill/Mouth bars that cut through the underlying strata. Two major parasequences were identified, the first lower one was developed during a shallowing upward sequence represented by shale/sand intercalations into which the main Abu Roash “C” reservoir sand bodies are included, and reached its end by the appearance of a laterally extended coal marker nearly one meter thick. This parasequence was deposited subsequently to a falling sea level phase which occurred after the deposition of Abu Roash “D” limestone. The succeeding parasequence (deepening upward) reached its maximum flooding surface (MFS) by the deposition of the widely extensive shale marker being rich in pelagic Pelecypod shells. The resultant stratigraphic units consist of: genetically related depositional cycles (3 cycles) and their components of facies sequences (5 facies types), each cycle has its own distribution, facies classification and reservoir characteristics. [ABSTRACT FROM AUTHOR]

Categorical variable modeling is of great significance for resource estimation as it defines a major aspect of geological heterogeneity and uncertainty. Stochastic simulation can be used to generate multiple equally-probable realizations that describe the uncertainty in the spatial distribution of categorical variables such as facies. These realizations reasonably sample the space of uncertainty if the input statistics are well known. However, the input statistics are often poorly defined due to sparse data. The prior parameter uncertainty related to proportions of different categories is required to achieve an accurate evaluation of the space of uncertainty. For decision making and risk analysis, it is critical to have an accurate and precise model of uncertainty associated with 3924 the subsurface geology. A methodology is proposed, implemented and checked to quantify parameter uncertainty related to facies proportions in presence of a locally varying proportion model (a trend model). Unconditional sequential indicator simulation (SIS) is employed to implement the spatial bootstrap and quantify the prior proportion uncertainty. A trend building algorithm provides multiple realizations of the trend model based on the spatial bootstrap realizations of sampled data. Passing this prior parameter uncertainty through geostatistical simulation provides a realistic posterior model of uncertainty that accounts for the data configuration, conditioning, spatial correlation, and the domain limits. [ABSTRACT FROM AUTHOR]

Abstract: High resolution reservoir models are often required for resource assessment and reservoir management. The reservoir models must reproduce geologically realistic heterogeneity that may affect predictions. An important heterogeneity in many deepwater depositional systems consists of facies variations controlled by geological events that lead to lobe geometries. A surface-based geostatistical scheme is presented to model high resolution lobes and their associated stacking patterns in a geometrically realistic manner. The lobes are constrained to match well data. Facies, porosity and permeability are then modeled within the lobe framework. Application to a reservoir with 36 wells demonstrates the practical applicability of the approach. This surface-based method may be readily extended to model other geometries in various reservoir settings. [Copyright &y& Elsevier]

Abstract: This paper presents an algorithm for the construction of event-based fluvial models. The event-based approach may be applied to construct stochastic pseudo-process-based fluvial models for a variety of fluvial styles with conditioning to sparse well data (1–5 wells) and areal and vertical trends. The initial models are generated by placing large-scale features, such as channels and crevasse splays, into the model as geometric objects. These large-scale features are controlled by geometric input parameters provided by the user and are placed into the model to roughly honor well data through a rejection and updating method. Yet, some model to well data mismatch may still occur due to inconsistency in the size and positioning of complicated features relative to the well data. An image processing algorithm is used to post-process realizations to exactly honor all well data. The final, cell-based models, have no data mismatch and contain geologically realistic fluvial features that would be difficult to obtain with other pixel-based methods and precise conditioning that is difficult to obtain with object-based methods. [Copyright &y& Elsevier]

This paper presents a FORTRAN program for hierarchical object-based modeling of complex fluvial facies. Unique features of this program include (1) a simple approach to place channel, levee, and crevasse sands within a matrix of floodplain shales, (2) templates for fast rastering of fluvial facies objects, leading to fast CPU times, and (3) the use of simulated annealing and non-random perturbation rules for conditioning to extensive soft facies-proportion data and local well data. Object-based modeling techniques are widely applicable to modeling fluvial depositional systems. Public domain software for such modeling is uncommon and inflexible with respect to the variety of conditioning data that can be handled. Commercial software is costly and also of limited flexibility. The fluvsim program overcomes many of these limitations with an accessible research code. [Copyright &y& Elsevier]

Shale and clay minerals as common constitute in the sandstones can be distributed in various scenarios which in turn can result in different reservoir and elastic properties. A new classification with distinct subclasses for clay distribution has been proposed based on the plausible configuration of shale/clay particles within the sandstone reservoirs. These subclasses give more quantitative insights into laminated, structural and dispersed clay scenarios by taking into account more details of the shale and clay microstructures. Some rock physics-based workflows were proposed and implemented on a real dataset to validate the given strategies to model different clay distribution types. These workflows can be used to generate a template in the elastic domain in order to differentiate various clay distributions. Accordingly, our dataset which was taken from a shaly sandstone in the Persian Gulf, was investigated in more details using the generated template for detecting different clay distribution types as well as observing different elastic and reservoir properties when clay distribution type is changed. We observed that there are four different classes (class I, II, III and IV) of properties with different trends in the crossplot of P-wave velocity versus porosity. Class I includes properties which their P-wave velocity increased when porosity is reduced. In contrast, class II includes properties which show a decreasing trend for P-wave velocity when porosity is reduced. Class III belongs to the properties with two different trends towards structural and dispersed clays. These properties do not follow the same trends for P-wave velocity changes versus porosity similar to classes I and II. However, when the given property decreases or increase by moving toward dispersed clay or structural clay, their P-wave may increase or decrease, respectively. Finally, class IV includes properties which their values do not show any particular trend within the given clay distribution types template. [Display omitted] • New topological classification for clay distribution based on plausible configuration of shale/clay particles. • Applicable in reservoir characterization workflows. • Several rock physics-based approaches proposed according to new classification. • A new rock physics template to differentiate various clay distribution. • Four different classes of reservoir and elastic properties of the rock as delineation attributes in sand-clay mixtures. [ABSTRACT FROM AUTHOR]

Gamma oil field is considered as oil producer from Nubia sandstone Formation. It lies in the southwestern part of the Gulf of Suez. The penetrated Nubia Formation in the available wells has good reservoir characteristics. It is mainly sand and shale (kaolinite) facies. Moreover, the porosity model reflects a good porosity in the area with values ranging from 11% to 22%. Conversely, the water saturation values show that all available wells are located under the oil-water contact and are highly saturated with water. Consequently, a 3D static model was carried out to distinguish the hydrocarbon distribution, mapping, and validate any Nubian sandstone reservoir upside exploration potential in the area. Accordingly, the property models and maps results show that the upside potential blocks at the southeastern direction reflected a highly promising for hydrocarbon prospecting where the water saturation values reflect an obvious decrease and the volumetric calculation of the OOIP (original oil in place) in the upside blocks is about 19.3 MMSTB, this reflects the economic importance of hydrocarbon accumulations in the Nubia sandstone Formation in the predicted area. • The Nubia formation composed of sandstone interbedded with thin streaks of kaolinite and has a good reservoir quality. • The Gamma oil field was affected by both the Clysmic fault trend and the Cross-faults trend. • The upside blocks at the southeastern part of the study area are very promising for hydrocarbon prospecting. [ABSTRACT FROM AUTHOR]

This study showcases the value of drone photogrammetry in creating a meter-scale geological model of complex carbonate geobodies. Although drone photogrammetry is now commonly used for modeling the sedimentary facies and architecture of sandstone outcrops, its use is not widespread in creating geomodels of carbonate geobodies. Drone photogrammetry can generate accurate line-drawing correlation and detailed architecture analysis along inaccessible vertical faces of outcrops and permits observations of unreachable places. This work models the Bathonian limestones of Massangis quarry (Burgundy) as an example. The quarry covers an area of 0.4 km2 and is considered as an analogue for the Oolithe Blanche geothermal reservoir in the center of the Paris Basin. The Massangis quarry model represents a good analogue for reservoir microporosity and secondary porosity associated with dedolomitization. Ten facies are described and grouped into three facies associations (1) clinoforms, (2) tidal to subtidal facies, and (3) lagoonal facies. The clinoforms are sets of very large marine dunes 15–20 m high that prograded N70° across the platform as part of a regressive systems tract. Moldic rhombohedral pore spaces associated with dedolomitization are well-expressed within clinoforms and in the bioturbated levels of lagoonal facies. Drone photogrammetry combined with the "Truncated Gaussian with Trends" algorithm implemented in Petrel® software is used to create a geological model that faithfully reproduces the facies architecture observed in the quarry cliffs. Drone photogrammetry can be combined with field work to describe and locate facies and so constrain the spatial distribution of petrophysical properties. It also helps constraining the shapes of geobodies in the model grid for more realistic geological static models and helps providing 3D petrophysical models from an outcropping analogue for geothermal and petroleum reservoirs. Image 1 • Drone-based photogrammetry in combination with VRGS® and Petrel® softwares. • High-resolution Digital Outcrop Modeling of 3D facies and sedimentary structures. • Clinoforms from giant, 15–20 m high marine sand waves prograding on the platform. • Analogue for carbonate-based geothermal and petroleum reservoirs. [ABSTRACT FROM AUTHOR]

The current work aims to study the structural and facies characterizations of the Apollonia Formation carbonate reservoir by applying the curvature attribute and facies modeling. This reservoir is considered an unconventional, gas-bearing chalk reservoir located at the JDT field in the Abu El-Gharadig Basin, northern Western Desert of Egypt. The workflow begins by computing the curvature seismic attribute on the available 3D seismic data of the field. This is accompanied by the detailed sedimentological and petrophysical analysis of available core data and the distribution of the resulting facies log along the available 3D geological model. The results of the curvature attribute along the Apollonia "A5" layer showed faults traces more than three times the traces determined by the variance attribute along the same layer, with small horizontal spacing between faults about 230 m. This attribute is considered as the best attribute for determining subseismic resolution faults (SSRF) of the polygonal faults affecting the reservoir. The facies analysis indicated that this chalk reservoir is composed of four primary facie: Faceis A (clean chalk), Facies B (slightly argillaceous chalk), Facies C (argillacesou chalk) and Facies D (marl). These facies had been differentiated form each other based on the clay percentage, porosity and permeability. The best reservoir facies are Facies A (clean chalk) with a clay percentage 0–5%, average porosity 31% and average permeability 0.43mD and Facies B (slightly argillaceous chalk) with a clay percentages 5–15%, average porosity 23% and average permeability 0.12mD. Distributing these facies along the JDT field declares dramatically that facies characterization of the lower pay zone is better than the upper pay zone because of the abundance of A- and B-type facies along the lower zone. Consequently, a 3D geological model had been constructed which used for the determination of the best location of any further development well targeting primarily A- and B-type facies and for any future production and hydraulic fracturing operations. • Application of Curvature attributes for the structural characterization of highly faulted carbonate reservoir. • Construction of 3D facies modeling for the lithological characterization of the carbonate reservoir. • The impact of these method on the reservoir development. [ABSTRACT FROM AUTHOR]

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. • Facies Modeling of Albian-Turonian successions in Lurestan province at the northwest of the Zagros fold-thrust belt, Iran is the main objective of this study. • Multi Resolution Graph Based Clustering (MRGC) techniques have been used for identifying electrofacies in reservoirs. • Sequence stratigraphy and age determination have been done based INPEFA log and the Zagros biozonation. • The Truncated Gaussian with Trend method has been used to distribute facies parameters. [ABSTRACT FROM AUTHOR]