This paper highlights 3D reconstruction of the paleo-topography of the depositional environment for a Lower Cretaceous carbonate formation onshore Abu Dhabi using 3D seismic and well data. The reconstruction was carried out for two reasons: (1) to understand underlying geologic causes for anomalous lateral variations in pressure, production performance, and logged reservoir properties in the field and (2) to delineate geologic trends away from well control in order to guide further decisions on field development and reservoir management options. Present-day structure of the reservoir top is a high-relief elongated anticline that is open to neighboring giant oil fields. Known hydrocarbon contact is below structural spill-point between the field and its neighbors, however pressure and production data indicate that the field is isolated from its neighbors. No fault was seen on seismic separating the field from its neighbors, thus raising possibility of stratigraphic separation. Further, study on core samples indicated that reservoir quality is controlled by depositional facies and early diagenetic modifications thereof. Thus, reconstruction of paleo-structure was conceived as a means of understanding and delineating geologic drivers for lateral variations in reservoir quality. The reconstruction process relied on an integrated approach: combining information from seismic, well logs, sedimentology, and well test results. Sedimentology studies gave information on expected morphology of depositional environment and controlling factors for reservoir quality; seismic interpretation of structure and stratigraphy at several levels provided basis to understand present-day field architecture and structural evolution through geologic time; reconstruction of three-dimensional structure at time of deposition was achieved by means of restorative velocity models to translate input mapped surfaces to their approximate original morphologies; results validation was achieved by subjecting study outputs to conformance tests with independent data from well logs, pressure tests, production performance, and seismic attributes trends. After reconstruction carried out in this study, the present-day steep anticlinal structure at the target reservoir was translated to a gently dipping ramp with morphology that is consistent with interpreted environment of deposition from cores. Outputs were further validated by conformance of well data and seismic attribute trends with the paleo-structure. Anomalous lateral variations in reservoir properties measured in wells were found to be associated with possible tidal channels that were interpreted to have caused localized diagenetic changes. Thus, findings from the paleo-reconstruction study provided a geologically consistent framework to understand lateral variation in well results, and also provided basis to guide further field development and reservoir management decisions as intended at study inception. Although outputs from the paleo-reconstruction process used in this study were deemed to have given good results, potential pitfalls in applying the method are herein noted.
Objectives/Scope Because of the complexity of properties and heterogeneities, the challenge in a carbonate reservoir is to predict the spatial distribution of the best reservoir facies. Due to the sparse distribution of wells, uncertainties exist, especially where fewer cored wells are available. The aim of this study was to employ machine learning, using the full dimensionality of 3D seismic data and well data, to predict lithofacies heterogeneities distribution in major reservoirs of the Thamama Group, for a recently developed large UAE onshore field. Methods, Procedures, Process This technology generates a probabilistic seismic facies model derived from the 3D seismic data. An association of naive neural networks, each with a different learning strategy, is run simultaneously, to avoid biasing any of the neural network architectures. To train the neural networks, seismic data and the lithofacies at the well location extracted along the wellbore are used as labelled data. To avoid overfitting from a limited dataset, we introduce seismic data away from the borehole (soft data) so that the neural networks can "vote" on their integration to improve the final training dataset before reaching the ultimate learning stage. Results, Observations, Conclusions The application of this technique on Lower Cretaceous carbonate reservoirs shows promising results. The analysis of the probability distribution gives good insights into reservoir facies distribution uncertainty. Lithofacies are created from electrofacies by subdividing facies based on hydrocarbons. The resultant prediction was validated through comparison with observations from a new drilled well, adding confidence in the decision-making process when selecting future drilling locations. This method uncovers new potential for seismic data reliability when predicting the reservoir lithofacies away from wells, especially when referring to prestack data with any type of seismic attributes. Using this method, the major reservoir lithofacies can be precisely predicted within the field. As the probabilistic facies model is calibrated to wells, this lithofacies data can be used for both geologic modeling and volumetrics analysis. Novel/Additive Information Machine learning techniques were successfully applied to generate lithofacies from electrofacies from the 3D seismic data, leading to accelerated interpretation and reservoir characterization processes. In many cases, they provided faster images of the subsurface while still maintaining accuracy, thus helping to improve the decision-making process when determining new drilling locations.
Based on the interpretation of 3D seismic profiles acquired in the northwestern area of the Ulleung Basin, East Sea, the shallow sediments consist of five seismic units separated by regional reflectors. An anticline is present in the study area that documents activity of many faults. Bottom simulating reflectors are characterized by high RMS amplitude. Acoustic blanking with low RMS amplitude is distinctively recognized in the gas hydrate stability zone. Seismic attribute analysis shows that if gas hydrates are underlain by free gas, the high reflection strength and the low instantaneous frequency are displayed below the boundary between them. Whereas, if not, the reflection strength is low and instantaneous frequency is high continuously below the gas hydrate zone. Based on the spectral decomposition of the bottom simulating reflector, the high envelope at the specific high frequency range indicates the generation of the tuning effect due to the lower free gas content. Four models for the occurrence of the gas hydrate are suggested considering the slope of sedimentary layers as well as the presence of gas hydrate or free gas
Within the onshore area of Abu Dhabi lies a very large super-giant field with confirmed economic hydrocarbon production occurring from an Upper Jurassic formation. This study forms part of a larger body of work that focuses on addressing key uncertainties relating to the sedimentological heterogeneity and the diagenetic overprint within multiple undeveloped gas reservoirs in this formation. Sedimentological frameworks were established for each studied reservoir interval based on the description of c.2,300ft of core and previous reports of a further 700ft of core acquired from 9 cored wells following the N-S structural alignment of the asymmetric anticline structure of the field. In addition, a dataset of c.250 standard and a small subset of polished thin sections have been used to calibrate core textures, fabrics, sedimentology and petrographic characteristics of the sedimentary rocks. Also, SEM and cold cathodoluminescence analyses have been performed to refine the pore architecture and cement stratigraphy respectively. From the core description and reports, the carbonate fabrics have been classified using Dunham (1962) and Embry and Klovan (1971) carbonate textures along with a set of qualifiers to characterise depositional lithofacies. Individual lithofacies are then grouped into a suite of environmental lithofacies associations representing a range of depositional settings based on genetic similarities and by analogy with modern and known ancient environments. The Upper Jurassic reservoir has a broad bathymetric range of depositional settings suggesting a relatively high angle carbonate ramp system. The succession records the transgression from an outer ramp setting through a range of inner ramp (oolitic/grain shoal and lagoonal) to intertidal and supratidal sabkha settings. The Upper Jurassic formation is divided into 4 members, with a different character; from the base, the Y unit comprises stacked mud-dominated fabrics interpreted as offshore sediments with variable inner ramp contributions as tempestites. The X unit is the first of three large scale carbonate-evaporite couplets, comprising two smaller-scale couplets, the carbonate being dominantly intertidal with minor subtidal excursions before being capped by nodular supratidal anhydrites. The W unit comprises multiple small-scale carbonate-evaporite couplets with a dominant intertidal and microbial mat character with notable horizons rich in rhizoliths and marginal supratidal microbial anhydrite. The uppermost V unit comprises 4 small-scale couplets but is dominated by anhydrite, the carbonates being thin, but showing changes from grain-rich beach to intertidal and very rare subtidal environments. The vertical stacking of lithofacies associations provided an insight into the depositional evolution and, along with the recognition of key surfaces enabled the generation of a time based sequence stratigraphic framework for each interval. Calibration of these surfaces with wireline log responses allowed the definition of sequence stratigraphic surfaces (e.g. sequence boundaries, flooding and maximum flooding surfaces where appropriate) to uncored intervals in each reservoir unit. In order to provide quantitative data for assessing lateral facies distribution, lithofacies associations were interpreted in the uncored wells based on a combination of wireline log responses, stratigraphic principles and semi-deterministic depositional models derived from the cored intervals. The production of facies trend maps for each depositional sequence has been based on plotting geologically conditioned boundaries that mark the changing proportions of dominant facies across the field. These maps are supported by reservoir architecture cross sections that show 2D vertical and lateral facies relationships. The sequence stratigraphic framework and the facies mapping process establish the geological constraints for lithofacies association spatial distribution and thus mitigate uncertainties and establish additional sedimentological controls for properties population in the geological model that forms part of the larger study.
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