Thickness maps of Neogene and Quaternary sediments in the Kloštar Field (Sava Depression, Croatia)

Malvić, Tomislav; Jović, Goran

doi:10.1080/17445647.2012.710463

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…A map is a numerical model of an attribute's (e.g., porosity, permeability, thickness, structure) spatial distribution (Malvić and Jović 2012;Huysmans and Dassargues 2013). However, mapping an attribute is rarely the goal; rather, a map is used to make a prediction about the reservoir.…”

Section: Introductionmentioning

confidence: 99%

Thickness, porosity, and permeability prediction: comparative studies and application of the geostatistical modeling in an Oil field

et al. 2014

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Background: In this study, we applied the geostatistical modeling to analyze an oil field. The reservoir properties, thickness, porosity and permeability, were studied. Data analysis tools, such as histogram, scatter plot, variogram and cross variogram modeling, were employed to capture the interpretable spatial structure and provide the desired input parameters for further estimation. SK (simple kriging), OK (ordinary kriging), Sgism (Sequential Gaussian Simulation), SC (simple cokriging), OC (ordinary cokriging) and MM2 (Markov model 2) methods were applied to estimate reservoir properties. Estimation difference maps were generated to compare the results of each method, providing more straightforward realizations in a visual way.

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Section: Introductionmentioning

confidence: 99%

Thickness, porosity, and permeability prediction: comparative studies and application of the geostatistical modeling in an Oil field

et al. 2014

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“…All case reservoirs of lithostratigraphic units had been considered as vertically uniform sections, regardless of the selected variable. Such regional and local structural interpolation can be clearly observed on the map published for the Bjelovar Subdepression (hand-made interpolation given in [24]) or the Kloštar Structure in the Sava Depression [25]. In the same structure, even geostatistical sequential indicator simulation of porosity and thickness had been made with 2D interpolation [26].…”

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confidence: 83%

Application of the Modified Shepard’s Method (MSM): A Case Study with the Interpolation of Neogene Reservoir Variables in Northern Croatia

Malvić

Ivšinović²,

Velić

et al. 2020

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Interpolation is a procedure that depends on the spatial and/or statistical properties of the analysed variable(s). It is a particularly challenging task for small datasets, such as in those with less than 20 points of data. This problem is common in subsurface geological mapping, i.e., in cases where the data is taken solely from wells. Successful solutions of such mapping problems depend on interpolation methods designed primarily for small datasets and the datasets themselves. Here, we compare two methods, Inverse Distance Weighting and the Modified Shepard’s Method, and apply them to three variables (porosity, permeability, and thickness) measured in the Neogene sandstone hydrocarbon reservoirs (northern Croatia). The results show that cross-validation itself will not provide appropriate map selection, but, in combination with geometrical features, it can help experts eliminate the solutions with low-probable structures/shapes. The Golden Software licensed program Surfer 15 was used for the interpolations in this study.

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“…Since it uses local variance, the difference between the expected and estimated values is minimal. Geostatistical methods and their application in reservoir description are very well described in many papers [30][31][32][33][34][35][36][37][38][39][40][41]. From the distributed porosity in 3D model, average maps were created (see Figure 9).…”

Section: Porosity-thickness Mapsmentioning

confidence: 99%

Comparison of the Sweetness Seismic Attribute and Porosity–Thickness Maps, Sava Depression, Croatia

Zelenika¹,

Mavar

Brnada³

2018

Geosciences

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The sweetness seismic attribute is a very useful tool for proper description of the depositional environment, reservoir quality and lithofacies discrimination. This paper shows that depositional channels and turbidity sandstones deposited during the Upper Pannonian and Lower Pontian in the Sava Depression can be described using porosity–thickness and sweetness seismic attribute maps. Two studied reservoirs are of Neogene stage (“UP” reservoir of Upper Pannonian age and “LP” reservoir of Lower Pontian age) and located in the Sava Depression, Croatia. Both reservoirs contain medium to fine grained sandstones that are intercalated with basinal marls. A comparison of the sweetness seismic attribute and porosity–thickness maps show a good visual match with correlation coefficient of approximately 0.85. A mismatch was observed in areas with small reservoir thickness. This work demonstrates the importance of using porosity–thickness maps for reservoir characterization. The workflow presented in this work has wider applications in frontier areas with poor seismic data or coverage.

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Thickness maps of Neogene and Quaternary sediments in the Kloštar Field (Sava Depression, Croatia)

Cited by 6 publications

References 6 publications

Thickness, porosity, and permeability prediction: comparative studies and application of the geostatistical modeling in an Oil field

Thickness, porosity, and permeability prediction: comparative studies and application of the geostatistical modeling in an Oil field

Application of the Modified Shepard’s Method (MSM): A Case Study with the Interpolation of Neogene Reservoir Variables in Northern Croatia

Comparison of the Sweetness Seismic Attribute and Porosity–Thickness Maps, Sava Depression, Croatia

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