Characterization and geostatistical modeling of reservoirs in ‘Falad’ field, Niger Delta, Nigeria

This research aims at characterizing and modeling delineated reservoirs in ‘Falad’ Field, Niger Delta, Nigeria, to mitigate the challenge caused by the heterogeneous nature of the reservoirs. Seismic and well log data were integrated, and geostatistics was applied to describe the reservoir properties of the interwell spaces within the study area. Four reservoirs, namely RES 1, RES 2, RES 3 and RES 4, were delineated and correlated across four wells. The reservoir properties {lithology, net to gross, porosity, permeability, water saturation} of all the delineated reservoirs mapped were determined, and two reservoirs with the best quality were picked for further analysis (surface generation and modeling) after ranking the reservoirs based on their quality. Structural interpretation of the field was carried, nine faults were mapped (F1—F9), and the fault polygon was generated. The structural model showed the area is structurally controlled with two of the major faults mapped (F1 and F3) oriented in the SW–NE direction while the other one (F4) is oriented in the NW–SE direction. A 3D grid was constructed using the surfaces of the delineated reservoirs and the reservoir properties were distributed stochastically using simple krigging method with sequential Gaussian simulation, sequential indicator simulation and Gaussian random function simulation algorithms. Geostatistical modeling used in this study has been able to give subsurface information in the areas deficient of well data as the estimated reservoir properties gotten from existing wells have been spatially distributed in the study area and will thus aid future field development while also they are used in identifying new prospect by combining property models with structural maps of the area.

Impact of geomechanical heterogeneity on multiple hydraulic fracture propagation

To extract more gas from shale gas reservoirs, the spacing among hydraulic fractures should be made smaller, resulting in a significant stress shadow effect. Most studies regarding the stress shadow effect are based on the assumption of homogeneity in rock properties. However, strong heterogeneity has been observed in shale reservoirs, and the results obtained with homogeneous models can be different from practical situations. A series of case studies have been conducted in this work to understand the effects of mechanical heterogeneity on multiple fracture propagation. Fracture propagation was simulated using the extended finite element method. A sequential Gaussian simulation was performed to generate a heterogeneous distribution of geomechanical properties. According to the simulation results, the difficulty of fracture propagation is negatively correlated with the Young's modulus and Poisson's ratio, and positively correlated with tensile strength. When each of the multiple fractures propagates in a homogeneous area with different mechanical properties, the final geometry of the fracture is similar to homogeneous conditions. When the rock parameter is a random field or heterogeneity perpendicular to the propagation direction of fracture, the fracture will no longer take the wellbore as the center of symmetry. Based on the analysis of fracture propagation in random fields, a small variance of elastic parameters can result in asymmetrical propagation of multiple fractures. Moreover, the asymmetrical propagation of hydraulic fractures is more sensitive to the heterogeneity of Poisson's ratio than Young's modulus. This study emphasises the importance of considering geomechanical heterogeneity and provides some meaningful suggestions regarding hydraulic fracturing designs.

A 3D geological model of a structurally complex relationships of sedimentary Facies and Petrophysical Parameters for the late Miocene Mount Messenger Formation in the Kaimiro-Ngatoro field, Taranaki Basin, New Zealand

The present study investigates the reservoir characteristics of the Mount Messenger Formation of Kaimiro-Ngatoro Field which was deposited in deep-water environment. A 3D seismic dataset, core data and well data from the Kaimiro-Ngatoro Field were utilized to identify lithofacies, sedimentary structures, stratigraphic units, depositional environments and to construct 3D geological models. Five different lithologies of sandstone, sandy siltstone, siltstone, claystone and mudstone are identified from core photographs, and also Bouma sequence divisions are also observed. Based on log character Mount Messenger Formation is divided into two stratigraphic units slope fans and basin floor fans; core analysis suggests that basin floor fans show better reservoir qualities compared to slope fan deposits. Seismic interpretation indicates 2 horizons and 11 faults, majority of faults have throw less than 10 m, and most of the faults have high angle dips of 70–80°. The Kaimiro and Ngatoro Fields are separated by a major Inglewood fault. Variance attribute helped to interpret faults, and other seismic attributes such as root-mean-square amplitude, envelope and generalized spectral decomposition also helped to detect hydrocarbons. The lithofacies model was constructed by using sequential simulation indicator algorithm, and the petrophysical models were constructed using sequential Gaussian simulation algorithm. The petrophysical parameters determined from the models comprised of up to ≥ 25% porosity, permeability up to around 600mD, hydrocarbon saturation up to 60%, net to gross varies from 0 to 100%, majority of shale volumes are around 15–20%, the study interval mostly consists of macropores with some megapores and 4 hydraulic flow units. This study best characterizes the deep-water turbidite reservoir in New Zealand.

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.

Geostatistical modeling of porosity and evaluating the local and global distribution

Porosity is one of the main variables needed for reservoir characterization. For this volumetric variable, there are many methods to simulate the spatial distribution. In this article, porosity was analyzed and modeled in the local and global distribution. For simulation, Sequential Gaussian simulation (SGS) and Gaussian Random Function (GRFS) were applied. Also, kriging was used to estimate the porosity at specific locations. The main purpose of this work was to investigate the porosity to compare geostatistical simulation and estimation methods in a sandstone reservoir as a real case study. First, the data sets were normalized by the Normal Scores Transformation (NST) and stratigraphic coordinate. The model of experimental variograms was fitted in the vertical and horizontal directions. For the simulation methods, 10 realizations were generated by each method. The Q-Q plots were calculated, and both sets of quintiles (Target Porosity Distribution versus Porosity realization) came from normal distributions with the following correlation coefficients: 0.93, 0.94 and 0.97 related to GRFS, SGS and Kriging, respectively. The extracted variograms from realizations showed that the kriging couldn’t reproduce the variograms with global distribution. For local validation, the cross-validation was evaluated and three wells were omitted. The re-estimation of porosity was considered at located well logs through the well sections window where the kriging had a better performance with minimum error to estimate porosity locally. Finally, the cross-sectional models were generated by each algorithm which showed that the simple kriging tries to produce smoother distribution, whereas conditional simulations (SGS and GRFS) try to represent more global-detailed sections.

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.