2nd International Workshop in “Geoenvironment and
Geotechnics”, September 2008, Milos island, Greece

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Developing comput...
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2nd International Workshop in “Geoenvironment and
Geotechnics”, September 2008, Milos island, Greece

to record continu...
2nd International Workshop in “Geoenvironment and
Geotechnics”, September 2008, Milos island, Greece

Figure 3: Visualisat...
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2nd International Workshop in “Geoenvironment and
Geotechnics”, September 2008, Milos island, Greece

foresees the crea...
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Lindrobamvalgmasokmandevelopingcomputationalgroundwatermonitoringandmanagmentsystemforestonianoilshaledepositgeoenv08 100720105207-phpapp01

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  1. 1. 2nd International Workshop in “Geoenvironment and Geotechnics”, September 2008, Milos island, Greece 1 Developing computational groundwater monitoring and management system for Estonian oil shale deposit H. Lind, K. Robam and I. Valgma Tallinn University of Technology K. Sokman Estonian Oil Shale Company ABSTRACT Mining in Estonian oil shale deposit mainly takes place in the Ordovician, Keila-Kukruse aquifer. The aquifer is affected by mining and is fully dried out around the working mine areas (Perens and Savitski, 2008). The groundwater level is decreased down to 30 m, to the mine floor elevation using about 30 pumping stations (Lind, 2005). The pumping rate is very high depending on the season, ranging from 10 up to 40 m3 per ton of produced oil shale (Reinsalu et al., 2006). The Estonian oil Shale Company mined 15.5 million tons of oil shale in 2007 (Source: Estonian Oil Shale Company). In order to predict the effects, and avoid the social and environmental impacts, there is a need to continuously monitor the situation and run software simulations aiming at decreasing the pumping rate. This becomes even more important since the environmental taxes on usage of groundwater resources increase every year. Therefore, it is necessary to monitor groundwater level and quality, and develop a groundwater model for the overview of the situation during mine operations and also for a number of years after mine closure. 1. INTRODUCTION The aim of the research is to develop and reorganize monitored groundwater data by Estonian Oil Shale Company and build a dynamic groundwater model in order to create a sustainable groundwater monitoring and management system. The monitored data is used as input data for the hydrogeological modeling using the Visual ModFlow Professional software for the ac- tive and prospective mining areas. The goal for the model is to generate descriptive three and two dimensional dynamic water table maps depicting hydrogeological conditions, in order to provide information regarding the changes of the water dynamics (i.e. from the graphical maps of water flow directions), as well as diagrams and reports of water in- and outflow. Also information about the water exchange between mines is considered useful (Reinsalu and Valgma, 2003; Reinsalu, 2005), as well as the water income rate into working mines. Today the monitoring system used by Oil Shale Company is not very flexible to analyze the situation and to create a dynamic model; a MS Excel worksheet with diagrams and a static model of groundwater level was created previously. The research project presented here will create a systematic database for developing a computational groundwater model of the oil shale deposit for sustainable management. 2. INPUT DATA FOR MODELING In order to build up the groundwater model it is necessary to have a lot of detailed input data in a structured form. For a simplified model at least information about the geological layers, the hydraulic conductivity, observation wells, pumping wells and boundary conditions is needed. For importing the data into the Visual ModFlow software some data processing is required. For the monitored water level data until today simple MS Excel worksheets were used. Currently collected data did not allow analysis of the information and easy extraction of the needed output for groundwater modeling. A MS Access database was created in order
  2. 2. 2 2nd International Workshop in “Geoenvironment and Geotechnics”, September 2008, Milos island, Greece to record continuously monitored observation well data in a structured form. Also MapInfo and its addition Vertical Mapper are used to generate background information. For inserting already existing data, a comfortable layout was developed to copy the information from MS Excel worksheet into MS Access database. New observed records for a certain observation well will be added using a form, as there is no need to insert well number, information of aquifer and geography. Each observation well in the database has a unique identification number to use as a link in different query tables. Query tables are used to extract only the needed information from the main table; in addition, the monitored information at certain time is added using queries as filling the main database table with observed information at different time periods would be too complicated. Using query tables the information needed for groundwater modeling with Visual ModFlow software can be easily exported. Output can be given selectively by monitored time, by aquifer and by geographical well location. The database will be further developed to give seasonal average water level per observation well as the groundwater level varies seasonally. The MS Access database together with linked geographic data by MapInfo Professional software (Fig. 1) allows visualizing the well location on a two dimensional map. All information added to the main table of the described database can be presented. MapInfo is used to generate simple static groundwater level models, where the average water table elevations are generated from linked database as the Visual Modlow is rather inflexible to create simple static models. In addition, the user can not easily change interpolated data that Visual Modflow generates based on measured data. Figure 1: Map of oil shale deposit with observation well database linked with Access database. Figure 2: Groundwater model of Oil Shale deposit created with Visual ModFlow. 3. BUILDING A GENERAL GROUNDWATER MODEL Mathematical models have a key role in assessing the future behavior of a system to find effective operating conditions for sustainable development and management groundwater resources. Besides the importance of organizing mining operations, advanced groundwater monitoring and modeling techniques are useful for environmental impact assessments, while different infrastructure objects are planned to be build nearby closed and waterfilled underground mines. The groundwater model of an oil shale deposit is under development using the Visual ModFlow software. The developed model will be dynamic; the data obtained through monitoring can be used to rerun the model and obtain results in real-time. As the software takes into account different parameters, including geological, hydrological and hydrogeological data, it is necessary to restructure current databases and collect the additional input data necessary for the model. One of the difficulties when creating the model is to collect and process the information needed for building and running the model. The area of the model is 127 x 55 ≈7000 km2 which includes mined out and prospective areas of oil shale (Fig. 2). As the model area is large, the accuracy of the results will be low and, hence, the output will be used for a general overview of groundwater dynamics. The created model has a grid size 100x100 m and has five main layers - on top is the ground, below it a 1 m thick soil layer, then limestone and an oil shale layer. The bottom of the model is a water impermeable layer (mainly the Uhaku geological bed) (Fig. 3). For the grid layer information, previous research information cre-
  3. 3. 2nd International Workshop in “Geoenvironment and Geotechnics”, September 2008, Milos island, Greece Figure 3: Visualisation of the model layers – ground layer and layer of oil shale. ated with MapInfo Professional was utilized. Today line information available in the model includes rivers and streams, investigation areas and mined out areas (properties and boundary conditions for these areas can be added later) (Fig. 4). Also, observation wells have been added as calibration data for the model (Fig. 5). While adding the wells the following problem was encountered: the interpolated model domain was smaller than the actual observation well depth. Therefore not all wells are entered since the software is rather inflexible to enlarge the model boundaries. As the area of oil shale deposit is more than 2700 km2 the model can include only the basics for the general overview; when a detailed investigation is needed for a certain location a smaller model can be developed (extracted) from the larger model. As there is lack of data for the area surrounding the oil shale deposit it may be necessary to create inactive areas around the deposit. 3 Figure 5: Part of mined out and prospective area (Aidu opencast), observation wells can be seen. 4. WATER QUALITY MANAGEMENT When the mine will be closed down, the groundwater level will increase within two to four years up to the level as it was before the economic activities started (Reinsalu et al., 2006). Changing the groundwater regime during and after mining will result in an increase in certain chemical components of the groundwater. The 2004 data showed a higher rate of sulphate content, total Fe, total oil products and total phenol in the water sampled from the closed waterfilled - underground mine, which exceeded the drinking water norm (Reinsalu et al., 2006; Erg, 2005). Therefore it is also necessary to monitor the water quality in the closed mine and of the pumped water from the mine which is settled in settling basin before directing into nearby rivers or dikes. It is also necessary to monitor seasonal changes in the concentrations of chemicals in the mine water. Hence, the groundwater quality management program has been started in different parts of the oil shale deposit. The model of water dynamics will be developed further for managing groundwater quality. 5. FURTHER DEVELOPMENT Figure 4: Inserted line information - rivers, lakes, prospective and mined out areas. Coloured background describes ground elevation. Developing the management system the observed data should be gathered in a structured form to insert the specified input data into the groundwater model. To create a simplified model the following data should be collected: geological layers, hydraulic conductivity, observation wells, pumping wells and boundary conditions. Further development of the model
  4. 4. 4 2nd International Workshop in “Geoenvironment and Geotechnics”, September 2008, Milos island, Greece foresees the creation of a database of pumping wells to be inserted into the model. Pumping wells will show the influence and changes on the water level nearby the mine workings. Also the model will give information to optimize used pumping capacities and also reorganize the location(s) of the pumping stations where it is technically possible. More detail information will be gathered regarding the hydraulic conductivity at certain layers and areas and the parameters for some of the boundary conditions of the model like river, lake, amount of precipitation and aquifer groups. After specifying the input data the situation of model should be calibrated which requires the equal values of observed and calculated water table values. This requires running the software and analyzing the results several times before receiving any results. While the created model is very large and while it goes more and more detailed there can be limits on capacity of regular computer. 6. CONCLUSIONS A groundwater management system in Estonian oil shale deposit is necessary to be developed further in order to understand the groundwater dynamics and the changes in the concentrations of potential pollutants (either primary or as a result of chemical reactions between water and minerals, i.e. pyrite) in order to decrease and/or avoid any negative impacts. Groundwater usage is sustainable today, but it can become even more efficient by a) decreasing the influence of mining to people living nearby active mine areas whose drinking water wells could be dry or polluted and b) avoiding any negative impacts on environmentally protected areas. As the depression cone due to mining is very wide, influencing different environmentally protected areas, draining wells for drinking water etc, technological solutions like impearmable walls, infiltration dams, pumping water from mine back to the area should be applied to keep the water level. ModFlow helps to model this situation and thus make the right decisions regarding the application of these technological solutions. Furthermore, it should be noted that if there is a need to reach drinking water quality the technical solutions are available, while the cost and economical question should be considered. Computational mathematical models can be used to allocate the technical and environmental constraints. To conclude it should be mentioned that the software package will be used to have a computational groundwater model to simulate conditions at technogenic mining areas. Today is important to predict the influence to the environment before the mine starts working. The computational groundwater management system can be used while new mines are opened, current mining is progressed or to overview the situation at closed down mines especially if nearby building activity is needed. The output files from the software can be used to visualize the current and also the future conditions after geological changes by mining development. The output data can be used for economical calculations as well. The current project is done as part of the research “Conditions of sustainable mining” ETF7499, whose scope is to use computer modeling to form the basics for sustainable, environmentally friendly mining. REFERENCES Reinsalu, E. and I. Valgma, 2003. Geotechnical Processes in Closed Oil Shale Mines, Oil Shale, Tallinn: Estonian Academy Publishers, 398 - 403. Reinsalu, E., 2005. Changes in Mine Dewatering After the Closure of Exhausted Oil Shale Mines, Oil Shale, Tallinn: Estonian Academy Publishers, 261 - 273. Erg, K., 2005. Changes in groundwater sulphate content in Estonian oil shale mining area. Oil Shale, 22 (3), 275-289. Lind, H., 2005. The modelling of hydrogeological conditions. The case study of dewatering Tammiku Kose surface mine, Thesis, Estonian National Library. Reinsalu, E., I. Valgma, H. Lind and K. Sokman, 2006. Technogenic water in closed oil shale mines, Tallinn: Oil Shale, Estonian Academy Publishers Vol. 23. Perens, R. and L. Savitski, 2008. Põlevkivi kaevandamise mõju põhjaveele (in English: Oil Shale mining influence on groundwater). Keskkonnatehnika, 3/08, 4447.

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