APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD

<p align="justify">In the early stage of geothermal exploration, geoscientist was assigned to conduct an estimation potential of the field with utilizing a limited number and type of data, which are geological, geochemical, and geophysical data (3G) along with two to three gradient t...

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Main Author: SYAHRUR RAMADHAN (22615002), QODRI
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/30059
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Institution: Institut Teknologi Bandung
Language: Indonesia
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spelling id-itb.:300592018-09-28T13:17:44ZAPPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD SYAHRUR RAMADHAN (22615002), QODRI Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/30059 <p align="justify">In the early stage of geothermal exploration, geoscientist was assigned to conduct an estimation potential of the field with utilizing a limited number and type of data, which are geological, geochemical, and geophysical data (3G) along with two to three gradient temperature wells. In doing so, it will create an overestimate value of the field. Reservoir volume plays an important variable for the result of these calculations. Therefore, a relatively new approach to calculate geometry reservoir needs to be done to minimize error, in this case, geostatistical method offer a solution. <br /> <br /> <br /> The aim of this research are to create a reservoir geometry model and to calculate its volume. Reservoir geometry model generated into three models, which are one model from resistivity data by magnetotelluric (MT) cross sections and two models from temperature data which comes from temperature core hole (TCH) wells. Reservoir geometry from resistivity data determined by performing a delineation on MT cross sections to medium zone of resistivity values (15-100 &#937;.m), while the volume was calculated by frustum method. <br /> <br /> <br /> In the other two models with TCH wells data, it was done by applying geostatistical approach on two different dataset, which are dataset A (3 TCH wells) and dataset B (11 TCH wells). Those models will produce temperature blocks distribution in three-dimension (3D). The key factor on geostatistical model is to create a variogram model to generate variables for kriging estimation, which consist of sill, nugget effect, type of variogram model, and range. Reservoir volume from kriging estimation was obtained by block model filtering activities which has a temperature value more than 210oC. <br /> <br /> <br /> After three reservoir volumes obtained, then the electricity potential is calculated for each of the reservoirs. Estimated electricity potential calculation has been done by volumetric method and the result are electricity potential of 55 MWe, 46 MWe, and 31 MWe from MT cross section model, TCH dataset A, and TCH dataset B sequently. If the estimated potential are compared to the current production capacity by developer at this time, the estimation result have lower percentage in about 16-44%. Meanwhile, the result of the estimated potential carried out by EBTKE has a difference up to 155% of the current production v capacity. Based on the comparison result, then it can be concluded that the methods used in this study are better than EBTKE estimation result, and geostatistical methods is still possible to be applied at the beginning of exploration stage.<p align="justify"> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <p align="justify">In the early stage of geothermal exploration, geoscientist was assigned to conduct an estimation potential of the field with utilizing a limited number and type of data, which are geological, geochemical, and geophysical data (3G) along with two to three gradient temperature wells. In doing so, it will create an overestimate value of the field. Reservoir volume plays an important variable for the result of these calculations. Therefore, a relatively new approach to calculate geometry reservoir needs to be done to minimize error, in this case, geostatistical method offer a solution. <br /> <br /> <br /> The aim of this research are to create a reservoir geometry model and to calculate its volume. Reservoir geometry model generated into three models, which are one model from resistivity data by magnetotelluric (MT) cross sections and two models from temperature data which comes from temperature core hole (TCH) wells. Reservoir geometry from resistivity data determined by performing a delineation on MT cross sections to medium zone of resistivity values (15-100 &#937;.m), while the volume was calculated by frustum method. <br /> <br /> <br /> In the other two models with TCH wells data, it was done by applying geostatistical approach on two different dataset, which are dataset A (3 TCH wells) and dataset B (11 TCH wells). Those models will produce temperature blocks distribution in three-dimension (3D). The key factor on geostatistical model is to create a variogram model to generate variables for kriging estimation, which consist of sill, nugget effect, type of variogram model, and range. Reservoir volume from kriging estimation was obtained by block model filtering activities which has a temperature value more than 210oC. <br /> <br /> <br /> After three reservoir volumes obtained, then the electricity potential is calculated for each of the reservoirs. Estimated electricity potential calculation has been done by volumetric method and the result are electricity potential of 55 MWe, 46 MWe, and 31 MWe from MT cross section model, TCH dataset A, and TCH dataset B sequently. If the estimated potential are compared to the current production capacity by developer at this time, the estimation result have lower percentage in about 16-44%. Meanwhile, the result of the estimated potential carried out by EBTKE has a difference up to 155% of the current production v capacity. Based on the comparison result, then it can be concluded that the methods used in this study are better than EBTKE estimation result, and geostatistical methods is still possible to be applied at the beginning of exploration stage.<p align="justify">
format Theses
author SYAHRUR RAMADHAN (22615002), QODRI
spellingShingle SYAHRUR RAMADHAN (22615002), QODRI
APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
author_facet SYAHRUR RAMADHAN (22615002), QODRI
author_sort SYAHRUR RAMADHAN (22615002), QODRI
title APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
title_short APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
title_full APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
title_fullStr APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
title_full_unstemmed APPLICATION OF GEOSTATISTICAL METHODS TO ESTIMATE RESERVOIR VOLUME IN A GEOTHERMAL FIELD
title_sort application of geostatistical methods to estimate reservoir volume in a geothermal field
url https://digilib.itb.ac.id/gdl/view/30059
_version_ 1821995620626333696