Sudarto Notosiswoyo

Development of drain hole design optimisation: a conceptual model for open pit mine slope drainage system with fractured media using a multi-stage genetic algorithm

High rainfall in equatorial regions leads to high groundwater levels or pore pressures and a high risk of landslides on the slopes of open pit mines, hindering mining operations. To lower the groundwater level surrounding a slope, a drainage system is needed. A drain hole is a part of a drainage system which utilises gravity to drain groundwater. Drain hole installation in fractured media requires the determination of the number, location, length and other parameters of the drain holes. Drain holes are frequently installed in uniform configurations or in layouts with uniform spacing, which are often ineffective and uneconomical, as some holes are not in the right positions or directions within the fractured media. This paper attempts to develop a conceptual model of an optimised configuration of drain holes by setting the drain hole parameters, or decision variables, such as number, location and length, in such a way that it produces the most effective and efficient outcome by maximising groundwater lowering and minimising cost. The optimisation is supported by the multi-stage genetic algorithm method in combination with a groundwater simulator, hereafter called the multi-stage GWSim-GA SO method. The procedure of the conceptual model will be further developed and used as a framework in the groundwater management of fractured media of an open pit mine slope.

GIS modeling using fuzzy logic approach in mineral prospecting based on geophysical data

The geophysical exploration method is the superior over the project area due to the dense of vegetation and thick soil so very limited geological outcrops. Contrast of physical properties of every different rock type should be able to be distinguished by the geophysical data. Fuzzy logic approach and weight of evidence were used for geophysical data modeling. Posterior probability was used to calculate the weight of evidence (WofE) of every fuzzy map memberships. By combining each rock type model, the model provides better result compared from the model from mixed rock type on the data training. This method is able to eliminate the potential interference of different geophysical signature. So that, the understanding the geological feature of the area is key success for the mineral prosperity modeling. We verified the model by site visiting and drilling and it is estimated about 90% confident.

Hydrology Simulation of Ukud River in Lati Coal Mine

Development of mine pit and overburden disposal has caused dynamic changes in the catchment area of Ukud River, one of the rivers that flow through Lati Mining Operation. The maximum discharge of the river reached 13m3/second and the catchment area occupied a total area of 1901.7 hectares. Since the mining operations started, the river discharge fluctuations have changed considerably. In addition, the catchment area that was dominated by overburden disposal area contained sulphide minerals that potentially degrade the water quality of Ukud River due to the formation of acid mine drainage. Hydrological studies are essential to investigate potential environmental impacts of the mining activities. This study was conducted to determine the characteristics of the hydrologic systems in the mining area using semi-distributed models that can be used to simulate the river flow within catchment area.

Revisiting hydrostratigraphy in Bandung-Soreang groundwater basin: A well-logs re-analysis

An attempt to revisit the hydro-stratigraphy of Bandung-Soreang Groundwater Basin (BSGB) has been done based on 111 well-logging training dataset. Transformation of resistivity values from well-log data to relative porosity and permeability used Chillingarian approach and Baker-Hughes Atlas of log responses. Then boundary marker was drawn to separated different aquifer layers. Simple linear regression equations were derived from the transformation: (a) tuf layers: θ = −0.0023ρ + 2.5619, μ = −63.514θ + 167.38, σ = 22.912 μ + 238.78; (b) clay layers: θ = −0.0181 ρ + 2.6281, μ = −61.842 θ + 163.91, σ = 5.1202 μ − 11.503; (c) sand layers: θ = −0.0078 ρ + 2.5992, μ = −60.75 θ + 161.02, σ = 394.35 μ − 2156.8. Based on the new aquifer taxonomy, three hydro-stratigraphic units (HSU) and six sub HSU have been defined. UHs 1 is the top layer of the BSGB, located at elevation above 650 masl. It has three sub HSU that consists of tuf and sand. The permeability (K) values of this unit range from 0,0014 to 0.1 m per da...

Prediction of Fe and Cu Mineral Distribution Using Rock Physics and Geoelectrical Method: a Case Study in ModADA—Timika, Papua

Tailing is the waste generated from mining activities, and its presence in the world of mining cannot be avoided. As waste, it is considered to contain minerals rich in Fe and Cu. This research aims to reveal the metal distribution of both vertical and lateral, using geoelectric resistivity. From the results of chemical analysis of sediment deposition contains be 6.14%–8.88% of Fe metal and 0.16%–0.25% of Cu. It consist also around magnetite (34.35%–59.85%), Pyrite (18.3%–29.71%, Quartz (15.31%–25.43%), Garnet (1.73%–3%), Rutile (0.46%), Chalcopyrite (0.17%–1.46%), Pyroxene (0.8%–2.35%), Hematite (3.49%) and Iron oxide (1.80%–4.81%). Geoelectric data show a conductive layer with resistivity type between 1.38 ohm m‐47.3 ohm m. If this layer is correlated with well data, the deposition of sediment contains of Fe between 5.3%–8.2% and Copper between 0.18%–0.23%. This method is based on rock physics which done by correlating many laboratory experiment, field measurements and well data. Prediction of Fe and Cu...