Static reservoir modeling using stochastic method: a case study of the cretaceous sequence of Gamtoos Basin, Offshore, South Africa

Gamtoos Basin is an echelon sub-basin under the Outeniqua offshore Basin of South Africa. It is a complex rift-type basin with both onshore and offshore components and consists of relatively simple half-grabens bounded by a major fault to the northeast. This study is mainly focused on the evaluation of the reservoir heterogeneity of the Valanginian depositional sequence. The prime objective of this work is to generate a 3D static reservoir model for a better understanding of the spatial distribution of discrete and continuous reservoir properties (porosity, permeability, and water saturation). The methodology adopted in this work includes the integration of 2D seismic and well-log data. These data were used to construct 3D models of lithofacies, porosity, permeability, and water saturation through petrophysical analysis, upscaling, Sequential Indicator Simulation, and Sequential Gaussian Simulation algorithms, respectively. Results indicated that static reservoir modeling adequately captured reservoir geometry and spatial properties distribution. In this study, the static geocellular model delineates lithology into three facies: sandstone, silt, and shale. Petrophysical models were integrated with facies within the reservoir to identify the best location that has the potential to produce hydrocarbon. The statistical analysis model revealed sandstone is the best facies and that the porosity, permeability, and water saturation ranges between 8 and 22%, 0.1 mD (< 1.0 mD) to 1.0 mD, and 30–55%. Geocellular model results showed that the northwestern part of the Gamtoos Basin has the best petrophysical properties, followed by the central part of the Basin. Findings from this study have provided the information needed for further gas exploration, appraisal, and development programs in the Gamtoos Basin.

3D geo-cellular modeling for Oligocene reservoirs: a marginal field in offshore Vietnam

This study focuses on constructing a 3D geo-cellular model by using well-log data and other geological information to enable a deep investigation of the reservoir characteristics and estimation of the hydrocarbon potential in the clastic reservoir of the marginal field in offshore Vietnam. In this study, Petrel software was adopted for geostatistical modeling. First, a sequential indicator simulation (SIS) was adopted for facies modeling. Next, sequential Gaussian simulation (SGS) and co-kriging approaches were utilized for petrophysical modeling. Furthermore, the results of the petrophysical models were verified by a quality control process before determining the in-place oil for each reservoir in the field. Multiple geological realizations were generated to reduce the geological uncertainty of the model assessment for the facies and porosity model. The most consistent one would then be the best candidate for further evaluation. The porosity distribution ranged from 9 to 22%. The original oil place of clastic reservoirs in the marginal field was 50.28 MMbbl. Ultimately, this research found that the marginal field could be considered a potential candidate for future oil and gas development in offshore Vietnam.

Stratigraphic and structural control over permeability distribution in poorly consolidated siliciclastic rocks

Permeability models are very relevant for the characterization of oil systems. However, limitations related to the resolution of seismic data make it difficult to identify subseismic, sedimentary, and tectonic structures, which can significantly impact the flow pattern. This study analyzed the spatial variability of permeability according to stratigraphic and structural geology control to propose a useful model for poorly consolidated, fractured, and faulted siliciclastic reservoirs. In an outcrop analogue to this type of reservoir, air permeability was measured in 3 orthogonal directions at 24 points, spaced 2 m apart.The models were obtained by sequential Gaussian simulation (SGS) after statistical data treatment. The models were validated to ensure the consistency of the generated scenarios. Permeability values showed a positive asymmetric distribution and reduced medians toward tectonic structures. The fitted semivariogram model was exponential, with higher spatial continuity in the horizontal flow direction and lower in the vertical one. The permeability models emphasized the importance of considering subseismic structures in the flow analysis of reservoirs since they have proven to play a significant role in the permeability distribution in the outcrop assessed.

Median Polish Kriging and Sequential Gaussian Simulation for the Spatial Analysis of Source Rock Data

In this technical note, a geostatistical model was applied to explore the spatial distribution of source rock data in terms of total organic carbon weight concentration. The median polish kriging method was used to approximate the “row and column effect” in the generated array data, in order for the ordinary kriging methodology to be applied by means of the residuals. Moreover, the sequential Gaussian simulation was employed to quantify the uncertainty of the estimates. The modified Box–Cox technique was applied to normalize the residuals and a cross-validation analysis was performed to evaluate the efficiency of the method. A map of the spatial distribution of total organic carbon weight concentration was constructed along with the 5% and 95% confidence intervals. This work encourages the use of the median polish kriging method for similar applications.

Distribution of Antimony and Gold in Old Tailings and Heaps at the Milešov Locality (Příbram District)

Antimony ores were extracted and processed near the village of Milešov (Příbram district) for about twenty years in the second halfof the 19th century. Large heaps and a small sludge pond were left behind after this period. In 1988, this locality was inspected andsampled in order to gather information about residual resources of gold and antimony. The original archive data from this surveywere now studied again and interpreted using modern statistical and geostatistical methods. The interpolations methods chosenfor this purpose were inverse distance weighting (IDW), simple kriging and geostatistical sequential Gaussian simulation (SGS).These procedures allowed for a much more accurate determination of the spatial distribution of the elements or substances studied.The results showed significantly higher volumes and a more accurate localization of the studied elements in both bodies (heap andtailings). This procedure can be considered as the basis of a new methodology for the assessment of similar objects.