Interpolation of Small Datasets in the Sandstone Hydrocarbon Reservoirs, Case Study of the Sava Depression, Croatia

Malvić, Tomislav; Ivšinović, Josip; Velić, Josipa; Rajić, Rajna

doi:10.3390/geosciences9050201

Cited by 15 publications

(27 citation statements)

References 16 publications

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“…Consequently, the MSM will force gradual interpolation much more strongly for outliers (extremes), i.e., it will perform smoothing instead of bull-eyeing. Finally, let us look at the selection criteria of the interpolation algorithm for the small datasets in the same spatial area as selected for this work (Table 4, the Sava Depression, northern Croatia [3]): Table 4. Recommended interpolation methods for small input data set [3].…”

Section: Cross-validationmentioning

confidence: 99%

“…The interpolation methods used in the Croatian part of the Pannonian Basin System (CPBS) are described in [2], while the final specific interpolation method that we applied is presented in [3]. The IDW method is widely used in the CPBS for mapping geological variables, and its application is described in [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Even back in the Bjelovar Subdepression, when the thickness had been remapped by Kriging, it was done in 2D space (e.g., [27,28]). Finally, 2D interpolation in the same region as selected in this analysis, had been especially favourable when the input dataset was small, regardless of whether the interpolation was done by statistical or geostatistical methods [3,19].…”

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confidence: 99%

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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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Section: Cross-validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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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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“…MSE, e.g., [4,9,10]). This value is often criteria for the most appropriate map selection in the CPBS (e.g., [11,12]).…”

Section: Cross-validationmentioning

confidence: 99%

“…Permeability (left) and injected volumes (right) maps interpolated using IDW, NN and NaN in reservoir "L" -present-day values[12] …”

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confidence: 99%

Increasing Efficiency in the Field Water Re-injection during Mature Hydrocarbon Reservoirs Water-Flooding, Case Study from the Sava Depression, Northern Croatia

Malvić¹,

Ivšinović²,

Velić³

et al. 2019

Preprint

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Here is analysed the process of water re-injection in the two hydrocarbon reservoirs/fields in the Upper Miocene sandstone reservoirs, located in the western part of the Sava Depression (Croatia). Namely, those are the "A" field with "L" reservoir and the "B" field with "K" reservoir. Both currently produce hydrocarbons using a secondary recovery method, i.e. water injection (in fact re-injection of the field waters). Three regional reservoir variables had been analysed, namely porosity, permeability and injected water volumes. The number of data was small in all three cases. For porosity: reservoir “L” included 25 data, reservoir “K” 19 data; for permeability: reservoir “L” 10 data, reservoir “K” 18 data; for injected volumes of water: reservoir “L” 10 data; reservoir “K” 3 data. It defined selection of mapping algorithms mostly designed for small datasets (less than 20 points), i.e. Inverse Distance Weighting, Nearest and Natural Neighbourhood. Additionally, the Ordinary Kriging was used, but only with jack-knifed variograms, producing many “artificial points”. Results are extensively tested, using cross-validation and shape recognitions, and the Inverse Distance Weighting method is described as the most appropriate approach for mapping permeability and injected volumes in both reservoirs (“K” and “L”). The Kriging could be slightly outlined as the best approach for porosity. Obtained maps made possible application of the modified geological probability calculation as tools for prediction of successfulness of future injection (probability of 0.56). Consequently, results made possible to plan future injection more efficiently, with smaller injected volumes and same of higher hydrocarbon recovery. That could prevent useless injection, decrease number of injection wells, and save energy and funds invested in such processes.

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A flexible and efficient model coupling multi-type data for 2D/3D stratigraphic modeling

Yan,

Guan,

Zhou

et al. 2024

Bull Eng Geol Environ

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Interpolation of Small Datasets in the Sandstone Hydrocarbon Reservoirs, Case Study of the Sava Depression, Croatia

Cited by 15 publications

References 16 publications

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

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

Increasing Efficiency in the Field Water Re-injection during Mature Hydrocarbon Reservoirs Water-Flooding, Case Study from the Sava Depression, Northern Croatia

A flexible and efficient model coupling multi-type data for 2D/3D stratigraphic modeling

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