GEOTHAI 07 International Conference on Geology of Thailand: Towards Sustainable Development and Sufficiency Economy APPLICATION OF RESISTIVITY SURVEY TO INVESTIGATE SINKHOLE AND KARST FEATURES IN SOUTHERN THAILAND : A CASE STUDY OF PAKJAM AREA Kachentra Neawsuparp and Tanad Soisa Department of Mineral Resources, Bangkok 10400, Thailand. ABSTRACT 2D and 3D resistivity imaging can be used to identify buried sinkholes zone covered by karst terrain at Pakjam area, in southern part of Thailand. Approximately 15m of regolith overlies karstified bedrock at this site. Drilling result shows some of void containing with clay-filled in contact between regolith and limestone. Low resistivity (high conductivity) anomalies appear to coincide with clay filled fracture zone. Resistivity survey work well in delineating filled sinkholes, underlying weathered bedrock. Keywords : Sinkhole, Resistivity, Image, Trung, Thailand. INTRODUCTION Sinkholes are depressions on the land surface caused by water moving downward into cracks and passages in the limestone below. Some sinkholes form slowly by solution of the underlying carbonate rocks, other sinkholes develop as a result of the collapse of surface or near-surface material. There are two basic types of sinkhole-forming collapses: 1) bedrock collapses, and 2) regolith collapses. Bedrock collapses are rare and generally occur due to enlargement of cave passages in limestone. The enlargement causes the roofs above the passages to weaken and eventually collapse to create sinkholes. Regolith collapses are much more common than bedrock collapses and generally result from regolith falling into openings in the underlying limestone. In the areas where the water table is above the regolithbedrock contact, collapses often occur when the water table drops below the regolith-bedrock contact, either during droughts or during high-volume pumping. Physically, the collapses in this case are caused by loss of supporting for the regolith arches that span openings in the limestone. Karst features are one of the most widespread and often under evaluated geologic hazards in carbonate terrains. Geologic maps are the principal tools for displaying and conveying data important in understanding reasons for sinkhole distribution. Although hazards such as collapse sinkholes cannot be completely prevented, geologic maps that delineate karst features can be applied by policy makers and the public to develop strategies to minimize or avoid loss. Resistivity techniques have been widely used to map the locations of sinkholes in covered karst terrain. To determine whether a sinkhole is a likely preferential channel for groundwater flow, however, requires higher-resolution imaging than that used in conventional sinkhole mapping surveys. 2D resistivity surveys clearly show the central depression as well as resistivity contrasts between the cover sediments within and outside of the sinkhole A growing number of investigations are employing resistivity survey to map these types of features. For example, Panno et al. (1994) used resistivity profiling to identify sinkhole-prone areas in southern Illinois: high resistivity zones correlated with air-filled cavities in the overburden that had formed over a bedrock conduit. Carpenter et al. (1998) used resistivity, GPR and EM surveys to identify filled sinkholes that were probable recharge points near Oak Ridge, Tennessee. Recently a number of papers have used two-dimensional (2D) resistivity imaging to examine sinkholes and the underlying weathered, or epikarstal, bedrock (e.g. Labuda and Baxter, 2001; Van Schoor, 2002; Zhou et al., 2002; Ahmed and Carpenter, 2003). This study investigates the use of resistivity survey to delineate filled or buried sinkholes to depths of about 25 m at Pakjam area, Trung province. The ability of 2D and 3D electrical resistivity imaging of fractures, caves and soil pipes associated with these filled sinkholes are also examined. STUDY AREA The study area is at Ban Pakjam in Huaiyod district, Trung province. The investigation area covers about 1 sq km. located between UTM 570000E-571000E and 850000N-851000N as shown in figure 1. The area is covered by alluvium deposit (Qa) and around the area is Ordovician limestone (O) formed as high mountains. The collapsed sinkhole in this area is approximately 10m wide and 3m deep at UTM 570315E /850430N. 19
Figure 1 The location map of Ban Pakjam area. METHODOLOGY The Pakjam area was selected to obtain detailed resistivity cross-sections over known and suspected filled sinkholes. The resistivity imaging was followed up with drillings, to verify the accuracy of the resistivity models. Resistivity surveys were performed with an automated multielectrode switching system (IRIS syscal R1 plus). The dipole-dipole array was chosen based on previous work that showed good resolution of epikarstal fracture and caves with this configuration (e.g. Roth et al., 1999; Labuda and Baxter, 2001). A total of 48 electrode positions with a dipole spacing of 5m were used. The raw apparent resistivity dipole-dipole data were inverted and interpreted using the rapid two-dimensional (2D) resistivity inversion least squares method (program RES2DINV, Ver. 3.3 [Loke, 1998]) to acquire a 2D true earth resistivity inversion solution, which is then color grid. These 2D images may still contain distortions and artifacts of the modeling process. Values near the base of the section, for instance, often incorporate 3D effects or off-line information projected onto the section due to lateral current spreading at wide electrode spacing. Anomalies near the edge of models are also suspect since there are usually few data points available for the inversion in these areas. Different numbers of iterations with different inversion parameters are necessary to insure an anomaly near the edge is not a processing artifact. Some of the inversion parameters that may be changed to test a solution s robustness include damping factor, flatness, filters and the initial model for the inversion (Loke, 1998). Mesh sizes may also be changed. However, too many mesh elements results in a high degree of electrical equivalence, i.e. there are more unknowns than data points, thus very large uncertainties in cell resistivities. 20
RESULT 2D resistivity surveys clearly show the central depression as well as resistivity contrasts between the cover sediments within and outside of the sinkhole. Clay-filled fractures and caves are represented as high-conductivity (low resistivity) zone in the resistivity images. All of these fractures are below the water table, so the low resistivities may be due to infilling by clay, or water within the fracture. Resistivity survey with a 5m dipole spacing, however, does not provide sufficient resolution to pinpoint their location except to within a few meters. Figures 2 shows the example of inverted and resistivity models made from dipole-dipole surveys with a 5m electrode spacing in Pakjam area (line 12). In these figures the filled sinkhole appears as a conductive (low resistivity) zone above a conductive trough in the bedrock, which may indicate an enlarged fracture and its alteration halo. All of the interpreted sinkhole (void) under the surface can be display as three zone as shown in figure 3. The resistivity data also found at about 15m along the profile a zone of deep weathering with more resistive bedrock pinching out and hints of a large probably saturated soilfilled void at least 5m below the surface. The pinch out zone probably represents a narrow weathered joint or fracture between the two bedrock masses. Twelve of the anomalous features were identified on the dipole-dipole survey lines (Fig. 3). The anomalies ranged from a very high resistance anomaly to a low resistance anomaly. The interpretation of the anomalies, ranged from possible void, to sands and gravels spanning the soil/limestone interface, to lenses of coarse grain sediments, to a clay filled void. Drillings encountered relatively fresh bedrock at depths of about 30m, although an elongate clay-filled cave was encountered by one of the drillings. Drilling PJ3 also encountered clay-filled void at about depths of 8-12m and 14-16m (Fig. 4). Soft raveled soil was found at shallow in drillings confirming the karst potential and correspondence of the interpreted bedrock horizon from the geophysics and the direct drillings. This example demonstrates the value of using shallow geophysics to rapidly gather high-resolution subsurface information in much greater detail than what can be obtained by a few drillings. The geophysics easily found a few high sinkhole potential anomalies that probably would have not been detected by randomly placing drillings as is often done in the industry. The electrical resistivity method found at the first anomaly a significant developing karst feature that almost certainly would have been exacerbated by standing and infiltrating water in the overlying basin probably causing failure of the basin through sinkhole development. As a result of the geophysical investigation, the location, shape and design of the basins is under review. The 2D surveys assume that all structures are infinitely long and perpendicular to the resistivity survey line. Because not all structures can be characterized in this manner and can be considerably more complex, 3D surveys can be conducted. The development of computer-controlled multi-electrode resistivity survey systems and the development of resistivity modeling software (Loke and Barker, 1996) have allowed for more cost-effective resistivity surveys and better representation of the subsurface. These surveys are typically referred to as Electrical Imaging surveys. Most resistivity surveys are collected as two-dimensional surveys. The modeling software also processes threedimensional surveys. These factors allow data to be collected and processed quickly, within a few hours, and as a result resistivity is becoming a more valuable tool in subsurface investigations. Drilling (PJ3) Potential sinkhole Bedrock Soft soil zone Possible weathered zone Figure 2 Resistivity image showing the location of drilling and interpreted sinkhole 21
Figure 3 The map of Pakjam area showing survey lines and interpreted sinkhole zones Inverse modeling of the data in this study is performed using RES3-DINV (Loke, 1997) to produce a threedimensional resistivity model based on the apparent resistivity data. Final data processing involves the generation of color-enhanced contour maps of the data using a two-dimensional mapping program. Resistivity models are presented in cross-section or 3D model blocks, with inline distance shown along the horizontal axis, depths, or elevation along the vertical axis. The geoelectrical model presents the electrical stratigraphy (electrostratigraphy) of the subsurface. Modeling software, RES3-DINV (Loke, 1997) and Voxler (Golden software, 1997-2007), was utilized to convert the measured apparent resistivities collected to modeled resistivity. The results are displayed in figure 5 and are presented as vertical 2D slices along the following locations of the model. In this paper, 3D resistivity surveys were successful at two separate sites (Fig. 5 and 6). A low resistivity feature is located in X-Z plane represent the N-S sinkhole zone. In figure 5, the feature is consistent with a bedrock fracture or a throat of a potential sinkhole feature. The 3D resistivity survey has proven a valuable tool for mapping top of rock, potential voids, and sinkhole throats prior to collapse. In areas of very complex subsurface features the 3D resistivity survey can provide a better representation of the subsurface features. 22
Figure 4 Drilling result of hole PJ3 showing the core loss in voids DISCUSSION Resistivity works well to identify the base and outline of sinkholes filled with dominantly coarse sediment (e.g. sands, gravels, chert fragments). Sinkholes filled with clayey or silty soils, resistivity was much effective in delineating the subsurface structure of these sinkholes. Resistivity at a dipole spacing of 5 m, however, Anomalies, particularly from fractures are smeared out in the resistivity images. A smaller dipole spacing with more measurement points may improve resolution of the fractures. Following the data collection and modeling, the electrostratigraphy information is used to interpret the potential subsurface stratigraphy of the traverses. In general, dry materials have higher resistivity than similar wet materials because moisture increases their ability to conduct electricity. This resistivity change, if indicated in the observed electrostratigraphy, can represent water table depths. Beneath the water table, clay-free silts and sands, and gravels will have a much higher resistivity than silts or clays under similar moisture condition because finegrained materials are better conductors. In the bedrock, competent rock will have a high resistivity. Saturated fractured or weathered rock would show a much lower resistivity than the competent rock. Very high resistivities can indicate air filled voids. The identified electric boundaries separating layers of different resistivities may or may not coincide with boundaries separating layers of different lithologic composition. These differences may result from the gradational presentation of the electrostratigraphy. Therefore, the electrostratigraphy can vary from the geologic stratigraphy, and caution should be exercised when reviewing and interpreting the electrical profiles. CONCLUSION On the basis of our site inspections, our knowledge of the area, and our integrated interpretation of the geophysical data, we conclude that the tested section of interstate overlies two reactivated karstic sinkholes. The gradual, but continual and visually detectable subsidence in the study area and the sub-pavement voids, are attributed to the upward-propagating, piping-removal of embankment soil (i.e., washout of the fine-grained fraction of the embankment fill) through this sinkhole. As far as the subpavement voids are concerned, we believe that the grouting program has effectively stabilized the shallow subsurface in the short term. Long-term mitigation should involve the redirection of surface run-off waters away from the median in the distress area and the underlying tunnel. 23
N Figure 5 3D resistivity image of survey line 1-14 in Pakjam area. N Figure 6 3D resistivity image of survey line 15-22 in Pakjam area. REFERENCES Ahmed, S. and Carpenter, P.J., 2003, Geophysical response of filled sinkholes, soil pipes and associated bedrock fractures in thinly mantled karst, east-central Illinois. Environmental Geology, 44, p. 705-716. Carpenter, P.J., Doll, W.E., and Kaufmann, R.D., 1998. Geophysical character of buried sinkholes on the Oak Ridge Reservation, Tennessee. Journal of Environmental and Engineering Geophysics, 3, p. 133-145. Golden software, 1997-2007., Voxler software program, Golden software Inc, Colorado. Labuda, Z.T. and Baxter, C.A., 2001, Mapping karst conditions using 2D and 3D resistivity imaging methods: in Powers, M., Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, Environmental and Engineering Geophysical Society, CD- ROM, Paper GTV-1 Loke, M.H., 1997, RES2DINV ver. 3.3 for Windows 3.1, 95, and NT, Advanced Geosciences, Inc., pp. 66.Reccelli- Snyder, H.L., Stahl, Beth. A., Leberfinger, Jeffrey, and Warren, Jeffrey, 1999, Electrical Imaging: Method foridentifying Karst and Other Collapse Related Features Near Roadways, 50th Highway Geology Symposium, Roanoake, VA Loke, M.H., 1998, RES2DINV version 3.3: Rapid 2D Resistivity and IP inversion using the least-squares method. Computer disk and manual, Penang, Malaysia. Loke M.H. and Barker R.D., 1996, Practical techniques for 3-D resistivity surveys and data inversion. Geophysical Prospecting, 44, p. 499-523. Panno, S.V., Wiebel, C.P., Heigold, P.C., and Reed, P.C., 1994, Formation of regolith collapse sinkholes in southern Illinois: Interpretation and identification of associated buried cavities: Environmental Geology, 23, p. 214-220. Roth, M.J.S., Mackey, J.R., Mackey, C., and Nyquist, J.E., 1999, A case study of the reliability of multi-electrode earth resistivity testing for geotechnical investigations in karst terrains. in Beck, B.F., Pettit, A.J. and Herring, J.G., Proceedings of the 7 th Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst, Balkema, p. 247-252. RES2DINV and RES3DINV version 3.54 program., 2004, Geoelectrical Imaging geotomosoftware. Van Schoor, M., 2002, Detection of sinkholes using 2D electrical imaging: Journal of Applied Geophysics, 50, p. 393-399. Zhou, W., Beck, B.F. and Adams, A.L., 2002, Selection of electrode array to map sinkhole risk areas in karst terranes using electrical resistivity tomography, in Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, Environmental and Engineering Geophysical Society, CDROM, paper 13CAV4. 24