MODELING. DESIGN AND OPTIMIZATION OF OPEN PIT MINE AT THAR LIGNITE FIELD

Abstract

Pakistan, a nation possessing nearly 200 billion tonnes of coal, mainly concentrated in Thar region having more than 175 billion tonnes of lignite resources, is facing acute electricity shortfall of 5-7 GW. The development of long-term exploitation and utilization strategy guide for Thar lignite field is a prerequisite for energy security of Pakistan. The current research work is an attempt to develop sustainable mining plans for the exploitation of Thar lignite, with special consideration to geological basin modelling, identification of suitable areas for different mining methods to minimize resource losses, and optimum pit limits for future projects. At present, twelve exploration blocks have been developed at Thar coalfield and each block is studied separately. This project/Block specific planning and design approach will have adverse effects on geological and economical resource of Thar lignite field. It is indispensable to assess the Thar coalfield as a whole, otherwise, modeling and designing of mines separately in each block, without the understanding of Thar basin characteristics, will certainly lead to serious resource deterioration problem. The research methodology comprises of four phases namely; Thar Resource Modeling, Demarcation of suitable areas for different mining operations, Energy Resource Modeling, and Pit Design & Optimizations. The first phase of research strategy aimed at production of resource model for entire Thar blocks, including 3D solid models for multiple seams and spatial distribution maps for various coal quality attributes by geostatistical method, ordinary kriging. Total seven lignite seams were modelled in 03 lignite zones of Bara formation. The seam#5 which is a main seam at Thar coalfield, contains 75% of entire 12 blocks lignite resource, having 22.15 billion tonnes. Block mean values are estimated by employing ordinary kriging technique whereas the obtained model variogram parameters were used in ordinary kriging equations. The resulting spatial map of ash content shows structured distribution and LCV map shows fair agreement with ash map except in block VI where high and low values of ash and LCV occur in close proximity. The moisture distribution reveals higher values in northern and southern parts whereas the central portion possesses lower moisture values. The sulphur content shows homogenous distribution with some higher sulphur patches at places. The kriging variance maps are generated to delineate areas of higher uncertainty. These maps could be helpful to devise further exploration programs. Blocks were checked on the basis of global averages and swath plot comparison. In second phase, the cumulative stripping ratio distribution map has been developed for Thar Coalfield to establish specific areas/sections for particular mining operations. On the basis of cut off stripping ratio of 10:1 m:m, it is concluded that 39.37% of total blocks area is suitable for surface mining and 58.53% is appropriate for underground mining and outside waste dumps, whereas 2.1% area is no coal zone, only suitable for outside waste dumping. Hence the developed map can be used a guide for block allocation to particular mining operation. In third phase, uncertainty associated with heating values of Thar lignite was quantified in term of probability and converted into energy equivalent. The basic idea, governing the energy resource concept is the conversion of lignite energy content expressed as lower heating value (LCV, kcal/kg) into the electric energy (MWh or GWh). The estimated calorific values may be subjected to variation and these variation may subsequently affect the end use of lignite. Sequential Guassian simulation was used to quantify the uncertainty and 95th and 5th percentile maps of calorific value distribution were generated as Optimistic and Conservative cases. The kriging estimations was regarded as Base case calorific value distributions. The simulation took considerable computing time as the number of grid nodes were 772,133. The 100 realizations were simulated for each node. The average e-type spatial distribution map of lower calorific values was found similar to kriged out map. In Base case scenario, the energy potential of surface mining area will be 17.48 million GWh and at 37% efficiency and 85% plant availability, it is sufficient for generating capacity of 50,000 MW electricity for 47 years, whereas generating life will be 44 and 51 years, if power plant efficiency is 35% and 40% respectively. The net energy potential in conservative scenario ranges from 12.22, 12.92 and 13.97 million GWh at power plant efficiencies of 35%, 37% and 40%. In optimistic case scenario, the energy potential of surface mining area will be 21.94 million GWh and at 37% efficiency and 85% plant availability, it is sufficient for generating capacity of 50,000 MW electricity for 59 years, whereas generating life will be 56 and 64 years, if power plant efficiency is 35% and 40% respectively. The fourth phase dealt with the optimization and design of different pits in entire Thar lignite field. The optimization work was carried out using Geovia Whittle. The maximum overall slope angle were adjusted at 24o. The lignite price and cost of mining at Thar were selected as USD 45 per tonne and USD 2.5 per bcm. In first run pit shell generation at surface mining area, 86 nested pits were generated with varying revenue factors ranges from 0.3 to 2. The economical pit shell (pit 11) at lignite price of USD 22.5, contain 7.71 billion tonnes with stripping ratio of 6.24, whereas the net energy potential is in the range of 6.5 to 12.7 million GWh under different scenarios and efficiencies.. The proposed open pit and waste dump locations at four exploration blocks by different companies will results in deterioration of about 209 million tonnes of lignite resource. In order to avoid resource loss, the pit optimization in allocated blocks (Block I and VI) were carried out to recommend revised planning for minimal resource deteriorations. With the revised planning of pits and waste dump locations, will results in saving of 141 million tonnes of lignite resource and equivalent energy in the range of 115,797 GWh to 215,887 GWh. The four distinct surface mining complexes were located in surface mining demarcated areas; namely SM-1, SM-2, SM-3 and SM-4. The Five (05) most economical pits have been identified in four (04) surface mining areas. The area SM-3 (comprising of Block VIII and IX) is the most suitable in terms of maximum total energy content (1,350,793 GWh), maximum lignite tonnage per unit area of pit and minimum associated waste per GWh generated. The second preference of resource exploitation should be given to SM-2 area, which is located at Block IV. Similarly 3rd, 4th and 5th priorities are given to SM-1East, SM-4, and SM-1West respectively. The proposed pit at SM-1East contain 493 million tonnes of lignite and equivalent base energy content of 584,010 GWh @ 37% power plant efficiency, whereas the proposed pits at SM-4 and SM-1West contains the base energy of 460,603 and 214,052 GWh respectively.