Improved 3D seismic attribute mapping by CRS stacking instead of NMO stacking: Application to a geothermal reservoir in the Polish Basin

Pussak, Marcin; Bauer, Klaus; Stiller, Manfred; Bujakowski, W.

doi:10.1016/j.jappgeo.2014.01.020

Cited by 25 publications

(20 citation statements)

References 45 publications

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“…Pussak et al . ). Ultimately, results from classification and mapping of seismic facies can be used to define geometric and petrophysical constraints for the construction of reservoir models.…”

Section: Introductionmentioning

confidence: 97%

“…Coléou, Poupon and Azbel ; de Matos, Osorio and Johann ; Pussak et al . ; Molino‐Minero‐Re et al . ).…”

Section: Introductionunclassified

“…The most common way to combine multi-attribute information is clustering analysis using statistical methods or neural network-based techniques (e.g. Coléou, Poupon and Azbel 2003;de Matos, Osorio and Johann 2007;Pussak et al 2014;Molino-Minero-Re et al 2018). Facies types identified by the clustering analysis can be mapped to show their distribution across the geological targets.…”

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confidence: 99%

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Wavelet transform‐based seismic facies classification and modelling: application to a geothermal target horizon in the NE German Basin

Bauer

Norden

Ivanova

et al. 2019

Geophysical Prospecting

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At the geothermal test site near Groß Schönebeck (NE German Basin), a new 3D seismic reflection survey was conducted to study geothermal target layers at around 4 km depth and 150°C. We present a workflow for seismic facies classification and modelling which is applied to a prospective sandstone horizon within the Rotliegend formation. Signal attributes are calculated along the horizon using the continuous Morlet wavelet transform. We use a short mother wavelet to allow for the temporal resolution of the relatively short reflection signals to be analysed. Time‐frequency domain data patterns form the input of a neural network clustering using self‐organizing maps. Neural model patterns are adopted during iterative learning to simulate the information inherent in the input data. After training we determine a gradient function across the self‐organizing maps and apply an image processing technique called watershed segmentation. The result is a pattern clustering based on similarities in wavelet transform characteristics. Three different types of wavelet transform patterns were found for the sandstone horizon. We apply seismic waveform modelling to improve the understanding of the classification results. The modelling tests indicate that thickness variations have a much stronger influence on the wavelet transform response of the sandstone horizon compared with reasonable variations of seismic attenuation. In our interpretation, the assumed thickness variations could be a result of variable paleo‐topography during deposition of predominantly fluvial sediments. A distinct seismic facies distribution is interpreted as a system of thicker paleo‐channels deposited within a deepened landscape. The results provide constraints for the ongoing development of the geothermal test site.

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Section: Introductionmentioning

confidence: 97%

“…Coléou, Poupon and Azbel ; de Matos, Osorio and Johann ; Pussak et al . ; Molino‐Minero‐Re et al . ).…”

Section: Introductionunclassified

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confidence: 99%

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Wavelet transform‐based seismic facies classification and modelling: application to a geothermal target horizon in the NE German Basin

Bauer

Norden

Ivanova

et al. 2019

Geophysical Prospecting

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“…Research of deep geothermal systems requires careful analysis of a number of key geological factors, where the quality of the data determining the reliability of the models [1][2][3]. In the case of thermodynamic analysis of heat accumulated in geothermal waters utilization [4][5], ex.…”

Section: Introductionmentioning

confidence: 99%

Impact of rock mass temperature on potential power and electricity generation in the ORC installation

Kaczmarczyk

2017

E3S Web of Conferences

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Abstract. The basic source of information for determining the temperature distribution in the rock mass and thus the potential for thermal energy contained in geothermal water conversion to electricity, are: temperature measurements in stable geothermic conditions, temperature measurements in unstable conditions, measurements of maximum temperatures at the bottom of the well. Incorrect temperature estimation can lead to errors during thermodynamic parameters calculation and consequently economic viability of the project. The analysis was performed for the geothermal water temperature range of 86-100°C, for dry working fluid R245fa. As a result of the calculations, the data indicate an increase in geothermal power as the geothermal water temperature increases. At 86°C, the potential power is 817.48 kW, increases to 912.20 kW at 88°C and consequently to 1 493.34 kW at 100°C. These results are not surprising, but show a scale of error in assessing the potential that can result improper interpretation of the rock mass and geothermal waters temperature.

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“…In many parts of the world both basic research, in order to understand geological structures better (Chowaniec, 2009;Zuber & Chowaniec, 2009;Sowiżdżał, 2010Sowiżdżał, , 2012Stankowski, 2012;Özgür & Çalışkan, 2013;Sowiżdżał et al, 2013;Pussak et al, 2014), but also works aimed at optimisation of geothermal systems in terms of their operation have been carried out (Tomaszewska & Pająk, 2012;Żbikows-ka et al, 2013;Demir et al, 2014;Baba et al, 2015). Fundamental issues are, for instance, geothermal potential estimates assisted by numerical modelling (Szczepański & Szklarczyk, 2006) and analysis of geochemical composition of groundwaters in the context of scaling and corrosion prediction in geothermal systems.…”

Section: Introductionmentioning

confidence: 99%

Modelling geothermal conditions in part of the Szczecin Trough – the Chociwel area

et al. 2015

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The Chociwel region is part of the Szczecin Trough and constitutes the northeastern segment of the extended SzczecinGorzów Synclinorium . Lower Jurassic reservoirs of high permeability of up to 1145 mD can discharge geothermal waters with a rate exceeding 250 m 3 /h and temperatures reach over 90°C in the lowermost part of the reservoirs. These conditions provide an opportunity to generate electricity from heat accumulated in geothermal waters using binary ORC (Organic Rankine Cycle) systems. A numerical model of the natural state and exploitation conditions was created for the Chociwel area with the use of TOUGH2 geothermal simulator (i.e., integral finite-difference method). An analysis of geological and hydrogeothermal data indicates that the best conditions are found to the southeast of the town of Chociwel, where the bottom part of the reservoir reaches 3 km below ground . This would require drilling two new wells, namely one production and one injection. Simulated production with a flow rate of 275 m 3 /h, a temperature of 89°C at the wellhead, 30°C injection temperature and wells being 1.2 km separated from each other leads to a small temperature drop and moderate requirements for pumping power over a 50 years' time span. The ORC binary system can produce at maximum 592.5 kW gross power with the R227ea found as the most suitable working fluid. Geothermal brine leaving the ORC system with a temperature c. 53°C can be used for other purposes, namely mushroom growing, balneology, swimming pools, soil warming, de-icing, fish farming and for heat pumps.

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Improved 3D seismic attribute mapping by CRS stacking instead of NMO stacking: Application to a geothermal reservoir in the Polish Basin

Cited by 25 publications

References 45 publications

Wavelet transform‐based seismic facies classification and modelling: application to a geothermal target horizon in the NE German Basin

Wavelet transform‐based seismic facies classification and modelling: application to a geothermal target horizon in the NE German Basin

Impact of rock mass temperature on potential power and electricity generation in the ORC installation

Modelling geothermal conditions in part of the Szczecin Trough – the Chociwel area

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