This work integrates seismic and well log data to establish a 3D reservoir model of the Q-Field, which is a prolific onshore hydrocarbon field situated in the Central Swamp Depobelt of Nigeria. The subsurface modeling focuses on the four principal clastic reservoir intervals of the Agbada Formation (D6200, D7000, D9000 and E2000), which was deposited in a deltaic to fluvio-deltaic system during Eocene. The seismic-based structural modeling inferred an extensional set-up dominated by NW–SE trending normal faults. Reservoirs are sand-dominated and laterally extensive, as interpreted from the 3D facies model. Well log-based petrophysical parameters were up-scaled and distributed stochastically using the Sequential Gaussian Simulation method to generate a 3D reservoir property model. Lateral and vertical heterogeneities of the reservoir properties were inferred from the 3D models. In general, the clastic reservoirs exhibit 18–22% porosity, 62–105 mD permeability, moderate to good net-gross thickness, and 36–74% water saturation. Hydrocarbon accumulation was primarily restricted within the anticlines. Gas-down-to exists in the upper three reservoirs (D6200, D7000 and D9000) at 10,577 ft (1 ft = 0.3048 m), 10,756 ft and 11,389 ft, respectively. Gas–oil and oil–water contacts in the E2000 reservoir were interpreted to be at 11,812 ft and 11,886 ft, respectively. Based on the hydrocarbon distribution, oil and gas-in-place volumes were estimated for all the reservoir intervals. The comprehensive 3D modeling work addressed the spatial distribution of the studied reservoir properties and can be directly useful for planning better the future wells for field development.

Static Reservoir Modeling of the Eocene Clastic Reservoirs in the Q-Field, Niger Delta, Nigeria

Underground CO2 storage is a promising technology for mitigating climate change. In this vein, the subsurface condition was inherited a lot of uncertainties that prevent the success of the CO2 storage project. Therefore, this study aims to build the 3D model under geological uncertainties for enhancing CO2 storage capacity in the Shahejie Formation (Es1), Nv32 block, China. The well logs, seismic data, and geological data were used for the construction of 3-D petrophysical models. The target study area model focused on four units (Es1 × 1, Es1 × 2, Es1 × 3, and Es1 × 4) in the Shahejie Formation. Well logs were utilized to predict petrophysical properties; the lithofacies indicated that the Shahejie Formation units are sandstone, shale, and limestone. Also, the petrophysical interpretation demonstrated that the $$Es1$$
 reservoir exhibited high percentage porosity, permeability, and medium to high net-to-gross ratios. The static model showed that there are lateral heterogeneities in the reservoir properties and lithofacies; optimal reservoir rocks exist in Es1 × 4, Es1 × 3, and Es1 × 2 units. Moreover, the pore volume of the Es1 unit was estimated from petrophysical property models, ranging between 0.554369 and 10.03771 × 106 sm3, with a total volumetric value of 20.0819 × 106 sm3 for the four reservoir units. Then, the 100–400 realizations were generated for the pore volume uncertainties assessment. In consequence, 200 realizations were determined as an optimal solution for capturing geological uncertainties. The estimation of CO2 storage capacity in the Es1 formation ranged from 15.6 to 207.9 × 109 t. This result suggests the potential of CO2 geological storage in the Shahejie Formation, China.

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CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

The Quaternary stratigraphic unit is an important underground space resource for sustainable urban development. It is of great significance to understand the spatial variation characteristics of the Quaternary stratigraphic structure and its internal attributes. However, due to the openness and complexity of the Quaternary sedimentary environment, the sedimentary characteristics of Quaternary stratigraphic units are often very complex and difficult to accurately analyze. In this study, a method for analyzing Quaternary sedimentary characteristics via 3D geological modeling based on vector and grid integration is proposed. Based on this method, the Quaternary depositional framework of Xiong’an New Area is established. The results show that the study area is mainly composed of seven Quaternary strata with different sedimentary origins, and the 3D spatial variation characteristics of lithology in each stratum are unique. Taking the vector framework model as the constraint boundary, this study constructs the lithology stochastic model of each Quaternary stratigraphic unit respectively, and accurately simulates the 3D spatial variation characteristics of the inner lithology of Quaternary stratigraphic units in the study area, which is of great significance for the urban planning, construction, and environmental protection of Xiong’an New Area.

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Quaternary Depositional Framework of the Xiong’an New Area: A 3D Geological Modeling Approach Based on Vector and Grid Integration

Mapping of geochemical anomalies is crucial to exploration and environmental geochemistry. The complex geochemical landscape, multiple geological sources and various secondary surficial processes impose a certain degree of spatial uncertainty in mapping of geochemical anomalies. Quantifying such uncertainty is significant for improving the efficiency of environmental monitoring or mineral prospecting. In this paper, sequential indicator simulation (SISIM) was used to assess local and spatial uncertainties of geochemical anomalies, and the concentration–area (C–A) fractal model was employed to determine geochemical threshold prior to SISIM analysis. To illustrate uncertainty of Ag geochemical anomalies, Ag concentration data of 1,880 soil samples collected from northeast of Dong Ujimqin Banner district of Inner Mongolia, North China, was used in this study. Based on a set of simulation realizations of Ag concentrations, it was concluded that areas with low local (i.e., single location) uncertainty of Ag concentrations have low risk for mineral exploration. However, the spatial uncertainty for multi-locations showed that the joint probability statistics were stricter than local uncertainty. Therefore, combining local probability and spatial joint probability for delineating geochemical anomalies of Ag is more acceptable and reliable. The hybrid approach using C–A fractal model and SISIM provides a new way to delineate anomalous areas considering uncertainty of spatial distributions of geochemical elements.
 
 Thematic collection:
 This article is part of the Applications of Innovations in Geochemical Data Analysis collection available at:
 https://www.lyellcollection.org/topic/collections/applications-of-innovations-in-geochemical-data-analysis


Modeling spatial uncertainty of geochemical anomalies using fractal and sequential indicator simulation methods

The well-known “lost circulation” problem refers to the uncontrolled flow of whole mud into a formation. In order to address the problem related to the paucity of available data, in the present study, a model is introduced for the lost-circulation risk sample profile of a drilled well. The model is built taking into account effective data (the Block L). Then, using a three-dimensional geological modeling software, relying on the variation function and sequential Gaussian simulation method, a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses. 

Analysis of the Lost Circulation Problem

The study was carried out with the aim of predicting uncertainty using Sequential Indicator Simulation (SISIM) for lithofacies modelling, sequential Gaussian simulation (SGSIM) for reservoir property modelling and inferring the depositional environment using Flow Zone Indicator (FZI). Five well logs, core analysis data and 3D seismic data were used for the study. Reservoir sand named “Reservoir-E” was correlated across the five wells in the field, and its surface was mapped on the seismic sections from the 3D cube. Petrophysical evaluations revealed average, net to gross, porosity, permeability, the volume of shale, water saturation, hydrocarbon saturation (SH), Reservoir Quality Index (RQI) and FZI as 0.70, 0.29, 2342 mD, 0.158, 0.50, 0.50, 2.44 and 5.62 μm, respectively. Structural interpretations on seismic sections revealed five major faults which trend NE-SW, NW-SE and W-E. A 3D grid with dimension 204 × 120 × 5 = 122,400 was constructed to accommodate our model. Validation of lithofacies models shows a correlation coefficient of 89.43–92.98% for well data and model. The property model shows variability in effective porosity and permeability 0.24 to 0.38 and 560 to 5600 mD. The low amount of SH in well HT-2 and HT-3ST1 is attributed to the presence of baffles with low reservoir quality index with 1.81 and 1.67 for RQI and 5.05 and 5.27 for FZI as compared to well HT-1, HT-4ST1 and HT-5 with RQI of 3.61, 2.71 and 2.41 and FZI of 6.25, 5.85 and 5.66. The environment of deposition is interpreted to be mouth bar-upper shoreface. High porosity and permeability values are linked with high FZI and RQI which are targets for exploitation.

Application of sequential indicator simulation, sequential Gaussian simulation and flow zone indicator in reservoir-E modelling; Hatch Field Niger Delta Basin, Nigeria

Hilary Terkula Jika

Papers

Application of sequential indicator simulation, sequential Gaussian simulation and flow zone indicator in reservoir-E modelling; Hatch Field Niger Delta Basin, Nigeria