Demonstration of the Advanced Radio Imaging Method (RIM): Ground Truth Results for Three-Dimensional Imaging of Coal Seams

Transcription

1 Demonstration of the Advanced Radio Imaging Method (RIM): Ground Truth Results for Three-Dimensional Imaging of Coal Seams Joseph Duncan, RIM Geophysicist Larry G. Stolarczyk, President Stolar Horizon, Inc., Raton, NM Yi Luo, Research Associate Professor Syd S. Peng, Charles T. Holland Professor West Virginia University, Morgantown, WV

2 ABSTRACT Detection and assessment of severe geological anomalies ahead of a longwall face greatly benefits the mining operation. Electromagnetic-based Radio Imaging Method (RIM) is one of the most promising geophysical methods for this task. Based on two decades of development, the latest RIM instrumentation (RIM-IV) has expanded its operational range up to 1,800 ft. A site demonstration of the RIM-IV technology was recently conducted within a longwall panel. An extensive ground truth study was performed to evaluate the accuracy of the RIM survey results. This study compared the generated RIM tomograms of attenuation rate with the mapped geological anomalies. Three different approaches have been employed to examine the accuracy of the RIM results and to correlate the measured signal attenuation rates with physical properties of the coal seam. The study shows that the RIM-IV technology is able to identify and delineate those geological features that would severely affect the longwall mining operation. INTRODUCTION Unexpected geological anomalies, such as sandstone intrusions, fracture zones, sudden thinning of the coal seam, and frequent and severe seam undulations in a developed longwall panel can present severe difficulties for longwall mining operations. In order to detect geological anomalies ahead of a longwall mining operation, many geophysical methods have been developed and tested. The electromagnetic- (EM)- based Radio Imaging Method (RIM) is one of the most promising geophysical methods that can be applied to detect the geological anomalies in a longwall panel. Using this method, the zones of abnormally high attenuation rate are believed to correspond with the zones of severe geological anomalies. However, the previous versions of the RIM technology have some limitations that hinder their adoption in the mining industry. A new and much more capable RIM-IV technology has been developed and demonstrated at a longwall site. As a validation effort, the mapped geological anomalies have been compared with the tomogram images reconstructed with different compiler programs that employ two different tomography reconstruction algorithms. A preliminary examination of the tomograms was recently documented (Stolarczyk, et al., 2003). In this paper, the methodologies and results of a more comprehensive study employing three different methods to compare and correlate the attenuation rate and the geological factors are presented. Through such study, a better understanding of the ability and selectivity of the RIM-IV technology for detecting the mapped geological anomalies has been obtained. RIM-IV TECHNOLOGY Radio Imaging Method (RIM) in-mine instrumentation was developed twenty years ago. The principle of RIM technology is based on the fact that many of the geological anomalies offer much higher attenuation rate to the traveling electromagnetic wave than that observed in non-anomalous coal seams. Using sophisticated tomography reconstruction techniques, the location and dimension of these geological anomalies can be estimated. However, the early RIM technology was unable to detect geological anomalies in wide longwall panels (e.g., panel width larger than 1,000 ft). The latest man-carried instrumentation, termed RIM-IV, is achieved with wireless synchronization between the transmitter and a remote imaging receiver, as illustrated in Figure 1. Wireless synchronization provides for the RIM-IV receiver detection and measurement of the smallest possible signal embedded in electrical noise. The synchronous detection method maximizes the operating range of the RIM-IV instrumentation exceeding 1,800 ft in coal beds (Stolarczyk and Peng, 2003). The other important enhancements include its abilities to detect the changes of wave phase, and to consider the bending signal paths. Such enhancements make this technology useful in detecting geological anomalies in a three-dimensional space. Figure 1. Schematics of RIM-IV survey FIELD INSTRUMENTATION AND TOMOGRAMS RIM-IV Survey Site In order to demonstrate the RIM-IV technology in locating geological anomalies, a RIM-IV survey was conducted in a section of longwall panel being mined in the Pittsburgh coal seam. The selected survey area within the 1,082-ft-wide panel was 1,400 ft long, as shown in Figure 2. The mining direction in this panel was from right to left. The overburden depth in the survey area was about 600 ft. Based on mining experience in adjacent longwall panels, and the observations in gate road development near the survey site, a number of geological anomalies were anticipated to affect longwall operations. These geological features include: (1) a sandstone/silty shale intrusion into the main bench, (2) severe thinning of the main bench, and (3) severe rolling (undulation) of the 1

3 Zone 2 Zone 1 Zone 1A Figure 2. RIM-IV survey area and mapped geological anomalies main bench coal seam. It should be noted that the sandstone intrusion very often is the cause for the latter two types of geological anomalies. Generally, a draw slate (claystone type of rock) is sandwiched between the main bench coal seam and the roof coal. Normal mining procedure involves cutting the main bench, the draw slate, and some of the roof coal so that a relatively consistent mining height of about 6.5 ft is maintained. During the RIM-IV surveys, the transmitter was placed in the panel s headgate (belt entry), while the receiver was in the tailgate. A description of the RIM-IV survey equipment has been published elsewhere (Stolarczyk and Peng, 2003). Twenty-nine survey stations were arranged in the headgate as the transmitting points, while another 29 stations in the tailgate were used as receiving points. The spacing between the adjacent stations in the entries was 50 ft. The surveys were carried out in a manner that generated a dense web of radio wave propagation lines, termed ray paths. After the entire survey is done, a matrix of total signal attenuations (the difference of signal strength between the transmitter and receiver ends) can be 2 derived from the measured signal strengths along each ray path. Reconstructed s The first step in the interpretation of the RIM-IV survey data is to perform tomographic inversion of the measured signal attenuations for each ray path. In this step, the coal seam in the survey area is divided into n x m pixels, as shown in Figure 1. Through an iterative process, the attenuation rate (in db per 100 ft) in each of the pixels can be determined. The resulting attenuation rates in the pixels can be used to plot the tomograms of attenuation rate distribution in the survey area. As discussed in the previous section, the attenuation rate depends on a number of geological factors. The thinner the main bench seam, the higher the attenuation rate. The closer the sandstone layer/silty shale to the main bench, the higher the attenuation rate. The more severe the coal seam rolls, the higher the attenuation rate. It should be noted that all these factors could cause problems during longwall mining operation. However, the sandstone intrusion and the related rolling conditions of

4 the main bench are most closely tied to longwall mining productivity. The field survey data was used to construct ten attenuation rate tomograms using two software compilers with two different tomographic algorithms. Table 1 shows the construction methods for the 10 tomograms. Figure 3 shows tomogram 1D reconstructed by compiler A using the Algebraic Reconstruction Technique (ART) algorithm and four iterations. The warmer shades indicate higher attenuation rates, while the cooler shades are indicative of normal coal seam stratigraphy. Table 1. Construction Methods for the s Compiler Algorithm Number of Iterations/ Data Sweeps 1A A ART 4 iterations, Sweep 1 1B A ART 4 iterations, Sweeps 1, 2 1C A ART 4 iterations, Sweeps 1, 2, 3 1D A ART 4 iterations, Sweeps 1, 2, 3, 4 2A B SIRT 1 iteration 2B B SIRT 2 iterations 2C B SIRT 4 iterations 3A B ART 1 iteration 3B B ART 4 iterations 3C B ART 6 iterations GEOLOGY OF THE SURVEY AREA In order to calibrate the reconstructed tomograms generated from the RIM-IV survey data, extensive geological mapping was performed during mining through the survey site. The geological data in and around the RIM-IV survey site have been collected from the following three sources/means: 1. Eleven surface exploration boreholes located within 2,500 ft of the survey site. 2. Twenty-one underground roof scope-holes were drilled in the roof strata from the entries beside the survey site. Among the 21 scope-holes, 6 holes were located in the track entry on the tailgate side, 8 holes in the track entry, and 7 holes in the belt entry on the headgate side. Each of the scope holes was about 20 ft deep from the entry roofline. 3. Five profiles of geological anomalies along the longwall face. The five profile lines covered an area approximately 300 ft wide (parallel to the direction of mining). The exposed longwall face was mapped for the geological features, such as the thickness of the coal main bench, draw slate (mainly of shale or clay stone), roof coal, as well as the intrusion of silty stone and sandstone. The floor undulation along the longwall face was also surveyed. Based on the information, the geological anomaly profiles have been generated, as shown in Figure 4. It shows that a zone of intensive geological anomalies was located in the upper middle portion of the RIM-IV survey area. A severe intrusion of silty stone into the main bench was observed in the first three profiles near the panel tailgate. This intrusion caused severe thinning of the main bench to make it as thin as 0.78 ft. The intrusion also pressed the floor and roof strata downward to create a severe rolling condition there. The severe thinning of the coal seam and the rolling condition caused considerable problems to the longwall mining operations, as evidenced by the slow face advance rate Figure 3. s 1D (top: tailgate; bottom: headgate) Despite some variations in the distribution of the high attenuation rates within the 10 tomograms, there are some common observables. One similarity among the tomograms is a bent zone of higher attenuation rates from the upper right edge of the survey area down to the lower middle. Another similarity is a zone at the lower right corner of the survey area. Relative Elevation, ft Main Bench Coal Floor Elevation Floor Cut Main Bench Draw slate Silty Shale Roof Coal Potted Roof Distance from Headgate, ft Figure 4. Longwall face profile

5 The mapped geological anomalies in the RIM-IV survey area generated from the face profiling data, the measurements in the gate entries and cross-cuts, and information collected from previously mined longwall panels are also plotted in Figure 2. In this map, the geological factors that will adversely affect the longwall mining operation and mine safety are combined and shown in detail. The main factors of concern include the total thickness of the main bench, roof coal, and soft draw slate that can be easily cut by the longwall shearer. The purple zones represent areas where such total thickness is smaller than 3.0 ft, forcing the longwall shearer to cut considerable thickness of hard roof and floor rock for its passage. The red and red-hatched zones show the areas where this thickness is smaller than 5.5 ft, presenting an uncomfortable working environment. The purple, red, and red-hatched zones in Figure 2 are considered to be the areas of severe geological anomalies. It shows that these areas of severe geological anomalies started at the face location from to along the panel tailgate. The zones became narrower, less severe, and their trend turned westward as they traveled toward the headgate side. Their width was narrowed considerably to about 50 ft around the longitudinal center of the panel. The zones of geological anomalies were found between and in the panel headgate. It should be noted that another minor zone of geological anomalies was observed a short distance beyond the lower right corner of the RIM-IV survey area. These severe geological anomalies caused problems for the longwall mining operations as evidenced by the abnormally slow advance rate. For easy reference, the major zone of the severe geological anomalies that crossed the middle part of the RIM-IV survey area in Figure 2 is called zone 1, while the wider part of this zone near the tailgate is called zone 1A. The zone of geological anomalies outside the lower right corner of the survey area is called zone 2. The green zones indicate poor roof conditions or roof falls, while the yellow zones show that the sandstone is located very close to the roof line in Figure 2. The contour of the floor elevation is also plotted in this map showing abnormal undulations in the face profiles, especially near the tailgate side of the panel. Severe rolling of the coal seam also presented problems for longwall mining operations. COMPARISON OF MAPPED GEOLOGICAL ANOMALIES AND RIM-IV TOMOGRAMS Distribution Pattern Comparison In order to verify the capability of the RIM-IV technology in detecting geological anomalies ahead of longwall mining, the mapped geological anomalies in the RIM survey area (Figure 2) are compared to the reconstructed tomograms. s of attenuation rate depend on the software compiler, reconstruction algorithm and models used, and the number of iterations employed. This dependence was evaluated in order to find which combinations of algorithms, models, and number of iterations would produce a tomogram that can be used to detect and delineate the geological anomalies more accurately. Visual comparison is made by overlaying the reconstructed tomogram images over the plotted geological anomalies in the survey area. A main high attenuation zone is shown near the upper edge of the survey area in all the tomogram images, but shifts away from the severe geological anomaly zone 1 to the inby side (right). In some of the images (1A, 1B, 1C, 1D, and 3A), this high attenuation zone is located close to the zone of severe geological anomalies and there is a good agreement between the lengths of the wider part of the anomaly zone 1A and that of the high attenuation zones. In all other images, the location of the high attenuation zone is shifted toward the right more than 150 ft. This main high attenuation zone in images 1C, 2A, 2B, 2C, 3B, and 3C also forms a bent pattern toward the headgate side similar to the mapped anomaly zone. Despite the location shift on the tailgate side, the lower end of this bent pattern is located near the same place as the zone of severe geological anomalies on the headgate side. In all images except for 3A, a high attenuation zone is also formed near the lower right corner or near middle of the right edge of the survey area. This zone can be considered to be influenced by the geological anomaly zone 2. Overall, tomogram images 1C, 1D (Figure 3), 3A, and 3C, all reconstructed with the ART algorithm, matched with the two mapped geological anomaly zones better than all other ones. Matching Scoring System In order to quantify the accuracy of any correlations drawn between the mapped geological anomaly zones and the reconstructed tomogram images, a matching scoring system is proposed. In this system, differences in location and dimensions between the matching geological anomaly zones and the zones of high attenuation rate in the tomogram images are considered. In this scoring system, the main emphasis is placed on geological anomaly zone 1, as shown in Figure 2. The center location and the width of this zone at the tailgate, middle of the panel, and headgate are measured. These measured values are compared to those of the high attenuation zone on the tomogram images at the same points. A location matching score is assigned based on the location difference between the zones of high attenuation and corresponding geological anomalies in the following scale: 4

6 Location difference, ft Location score, g l > The width matching score is determined according to the following equation. g w Wg Wt = 1 (1) W In Equation 1, W g is the width of the geological anomaly zone at the measurement point, and W t is the width of the matching high attenuation zone in the tomogram image. A matching score is also given to the length of the wider part of the geological anomaly zone 1 (zone 1A in Figure 2). For geological anomaly zone 2, one score between 0 and 1 is assigned depending on its development trend. The total matching score for each of the tomogram images is the summation of the location and dimension matching scores. A higher total score indicates that a better match exists between the zones of the mapped geological anomalies and the zones of high attenuation rate in the reconstructed tomograms. A perfect match requires a score of 8. g Table 2 shows the assigned scores and the total scores for each of the tomogram images. It shows that image 1D has the highest matching score (5.69 out of the maximum of 8), while image 2C has the lowest score (3.77). The rank of the matching scores agrees well with the preliminary comparisons. Based on the visual examinations and the matching scores, the ART tomography reconstruction algorithm performs better than Simultaneous Iterative Reconstruction Technique (SIRT) in identifying and delineating the combined geological anomalies that affect the longwall mining operations. Compiler A seems to work better than compiler B in this case. EFFECTS OF GEOLOGICAL FACTORS In this section, the individual effects of the three geological factors (i.e., main bench thickness, distance between the main bench and nearest sandstone/silty stone, and the seam undulation) on the distribution of the attenuation rate have been studied. Using the geological data collected from the surface boreholes, underground scope holes, and the selected points along the five profiles in the longwall face, two types of contour maps have been generated, i.e., the thickness of the main bench, and the distance between the main bench and the nearest sandstone in the roof. Effects of Thickness of Main Bench Figure 5 show the thickness distribution of the main bench of the coal seam in and around the survey area (indicated with the red rectangular box). In this figure, the darker areas represent zones of lower values (thinner coal seam in Figure 5). It shows that a strip of significant main bench thinning crosses the survey area from the upper right part to the lower left part of the mapped area. Another two main bench thinning zones are located near the right edge and the lower left corner, respectively. The distribution of the main bench thickness in the survey area has been compared with each of the tomogram images. The comparison shows that the distribution of the main bench thickness matched best with tomogram 1D (Figure 3). Table 2. Matching Scores for the Reconstructed s Image Zone 1 Tailgate Middle Headgate Location Width Location Width Location Width Zone 1A Length Match Zone 2 Location Match Match Score Match Match Match Match Match Match 1D C B A A C B A B C

7 Effects of Seam Undulation Because of the large sizes of the longwall face equipment, severe undulation of the coal seam could affect the longwall mining operation. A more severely undulating coal seam forces the radio signals to bounce from the boundaries of the waveguide (floor and roof) more frequently, thus increasing the signal attenuation rate. In order to provide a quantitative measure for the undulation of the waveguide, Equation 2 is proposed to express the undulation factor, ζ. It is related to the undulation curvatures of the lower and upper boundaries and the thickness of the waveguide. A more severely bent and thinner waveguide results in a higher ζ. Figure 5. Distribution of main bench thickness in and around the RIM-IV survey area Effects of Sandstone Intrusion Figure 6 shows the contour map of the distance between the main bench and the nearest sandstone/silty shale in the roof in and around the RIM-IV survey area. For those sandstones or silty shales that intruded into the main bench of the Pittsburgh coal seam, the distance is negative. In this figure, the major sandstone and silty shale zone starts from the upper right part of the survey area and ended near the lower middle part. This sandstone and shale zone is located very close to, and often intruded into, the main bench The roof sandstone is close to the main bench at the lower right, lower left edge, and upper left corners. Through comparison of this distribution pattern to the tomogram images, it is found that image 2C matched fairly well with the closeness of the sandstone/silty shale to the main bench. However, the zone of high attenuation rate appeared to shift toward the right some distance near the panel tailgate. 1 ζ = K f K r 2 m m Where: K f undulation curvature of coal seam floor K r undulation curvature of coal seam roof m main bench thickness Using Equation 2, the undulation factors along the five longwall face locations where the geological profiles were mapped have been determined. The distribution of the undulation factors in the profiled area that is much narrower than the RIM-IV survey area is plotted in Figure 7, along with tomogram images 1D and 3C in the same area. Image 1D shows a better match at the upper right corner, while 3C suggests a better match to the overall distribution pattern. (2) Undulation Factor 1D 3C Figure 6. Distance to nearest sandstone/silty shale Figure 7. Undulation factor versus tomograms 6

8 CORRELATION STUDIES 9 attenuation vs. coal thickness In the previous analysis, comparisons have been made between the distribution patterns of the mapped geological anomalies and the zones of high attenuation rates generated with different compilers, algorithms, and number of iterations. Although their locations and dimensions have been compared, no quantitative comparison was made. In this section, statistical analysis is used to quantify correlations between the geological factors of the anomalies mapped and the attenuation rates measured. The attenuation rate for each of the pixels in the surveyed area was collected for a number of selected tomogram images (1D, 2B, 3A, and 3C). The entire RIM-IV survey area was divided into 28 (longitudinal direction) x 22 (transverse direction) = 616 pixels. For the purpose of comparison, the thickness of the main bench, the distance between the main bench and the nearest roof sandstone, and the undulation factors for each of the pixels are also generated. Attenuation Rate versus Thickness of Main Bench In order to study the correlations between the attenuation rate and the three factors of geological anomalies (i.e., seam thickness, distance to nearest sandstone, and undulation factor), statistical studies were performed for the profiled area only where the undulation factor could be derived. The attenuation rates in the profiled area of image 1D are plotted against the seam thickness in Figure 8. A descending linear relationship is apparent even though the scattering of the data makes it a weak correlation as suggested by the linear regression (R2 = or R = ) in the figure. Such a descending trend agrees well with the theoretical relationship. Since the range variation of seam thickness in the profiled area is relatively small, a linear relationship is appropriate to represent a section of the power function curve. Attenuation Rate, db/100 ft Image 1D Linear (Image 1D) y = x R 2 = Main Bench Thickness, ft Figure 8. Relationship between main bench thickness and attenuation rate in the profiled area The results of the regression studies for the other three tomograms are listed in Table 3. A descending linear relationship appears to be a better idealization of the data for each image, but is not as good as the regression coefficient (R) for the 1D image (Figure 8). Attenuation Rate versus Distance to Nearest Sandstone Linear regressions have also been performed on the data of attenuation rate versus the distance between the main bench and the nearest sandstone for the selected tomograms, and the results are also listed in Table 3. It shows that the data from image 3A produces the best linear relationship between the attenuation rates and the distance to the nearest sandstone as suggested by the computed regression R 2 = (R = ). The negative slopes of the regression equations confirm the theorem that the sandstone and silty shale (containing a high percentage of sand particles) act as the leakage path for the EM radio wave from the waveguide. Such leakage would increase the attenuation rate in the area where the sandstone or silty shale is located very close to, or has penetrated into, the main bench. Table 3. Results of Single Variable Regressions for the Images in the Profiled Area Image 1D 2B 3A 3C Method Attenuation versus Main Bench Thickness Attenuation versus Distance to Nearest Sandstone Attenuation versus Undulation Factor Slope Intercept R Slope Intercept R Slope Intercept R original ft shift original ft shift original ft shift original ft shift

9 Attenuation Rate versus Undulation Factor In a severely rolling coal seam, the EM wave scatters more frequently causing higher energy loss through refraction and reflection before it reaches the receivers. Therefore, the attenuation rate in the severely undulating area should be higher. Regressions have been performed on the data and the results are listed in Table 3. The positive slopes of the four regression lines confirm the previous theorem. Among the four tomogram images, the data from image 3A show a better distribution pattern than the other three, while image 2B is the poorest one. Analysis of Shifting Phenomena It has been shown in the previous sections that the zones of high attenuation rate, especially the one in the upper right part of the survey area, appeared to shift to the right some distance from the mapped geological anomalies. In order to quantify this phenomenon, the data of attenuation rates for each of the selected tomogram images are shifted 50 ft to the right of their original locations. The shifted images are then statistically correlated with the three primary geologic factors. Linear regressions have been performed for each of the images, and the results are also listed in Table 3, along with those from the unshifted data. Two items from the regression results, the slope and regression coefficient R, can be used as the comparison criteria. A line with a higher slope (positive or negative) indicates that the dependent variable (attenuation rate) is more sensitive to the targeted independent variable, and therefore, the reconstructed tomogram can be used as a better indicator of that independent variable. As shown in Table 3, the resulting slope and R for the shifted image 1D are higher than those from its original image, indicating that the shifted tomogram is better for the interpretation of the variation of the coal seam thickness than the original one. The shifted images of 2B and 3C also indicate some significant improvements over the original ones. However, shifting of image 3A resulted in a slightly worse match than the original one. Among these images, 1D is the best for detecting the variation of the coal seam thickness both before and after the data shifting. The shifted attenuation rates are also compared with the distance between the main bench and the nearest roof sandstone. The results of the linear regressions are also listed in Table 3. Both the slope and R for each of the images show varying improvements due to the data shifting. image 3A is best among the four for detecting the sandstone/silty shale intrusion both before and after the data shifting. Linear regressions have also been performed on the data of undulation factor versus attenuation rates for the four selected tomogram images. The results are also listed in Table 3. Based on the analysis, image 3A can be used as the best indicator for the undulating conditions of the coal seam, while image 2B is the worst one for this task. By shifting the tomogram image 50 ft toward the right, the most improvement is achieved for image 1D. Multi-Variable Regressions In order to study the combined effects of the three geological factors on the attenuation rate, multi-variable linear regressions have been performed on the data from each of the selected tomogram images in the profiled area. The outputs for each of the regressions include the intercept and the three coefficients for main bench thickness, distance to the nearest sandstone, and the undulation factor. The accuracy of the regressions is reflected by the multiples R and R 2. The results of the multi-variable linear regressions are listed in Table 4. Overall, the data shifting always gives a better fit than that from the original data. The most significant improvement through the data shifting is observed from image 1D as R increased from 0.44 to Among the selected tomogram images, image 3A yields the best multiple correlations before (R = 0.69) and after (R = 0.72) the 50-ft data shift toward the right. Images 1D and 3C also yield satisfactory results after the 50-ft data shifting toward the right. Table 4. Results of Multi-Variable Regressions for the Images in the Profiled Area Image 1D 2B 3A 3C Coefficients for Accuracy of Regression Method Distance to Main Bench Undulation Nearest Thickness Factor Sandstone Intercept Multiple R R 2 original ft shift original ft shift original ft shift original ft shift

10 Based on the quantitative analysis performed in this section, the tomogram images that can be used to detect the individual or the combined geological factors are listed in Table 5. It shows that image 3A, reconstructed with compiler B, ART algorithm, and one iteration, is the best indicator for detecting sandstone intrusion, severely undulated seam, and the combined effects. Image 1D, reconstructed with compiler A and ART algorithm, performs better for detecting the variation of the thickness of the coal seam. Shifting the reconstructed tomogram 50 ft toward the right improves the detection accuracy. CONCLUSIONS A ground truth study has been performed in an effort to demonstrate RIM-IV technology in detecting geological anomalies ahead of longwall mining. Field surveys have been conducted in a section of the longwall panel where severe geological anomalies were expected. A number of tomograms of attenuation rate have been reconstructed using two compilers and two algorithms. The geological information in and around this testing site has been collected and mapped. The main efforts have been made to compare and to correlate the reconstructed tomograms with the mapped geological anomalies that could adversely affect the longwall mining operations. The measurable geological factors that have been studied are the thickness of the main bench coal seam, the distance between the main bench and the nearest sandstone, and the undulation factor of the main bench. The following three techniques have been employed to compare the tomograms and the geological anomalies: 1. Visual examination of the high attenuation rate distribution patterns and the zones of severe geological anomalies. 2. Matching scoring system to compare the locations and dimensions of the zones of severe geological anomalies and high attenuation rates. 3. Quantitative analysis that correlates each of the three geological factors and their combined effects on the attenuation rates. The study shows that the RIM-IV technology is capable of identifying and delineating the geological anomalies that affect longwall operations. The zones of high attenuation rates in the reconstructed tomograms appear to result from a combination of the three main measurable geological factors. However, a certain type of individual geological factor can be detected better with one particular type of tomogram than the others. Overall, the Algebraic Reconstruction Technique (ART) performs better than the Simultaneous Iterative Reconstruction Technique (SIRT). It has also been found that, for this particular data set, the high attenuation zones in most of the tomograms appeared to shift some distance away from the mapped anomalies. The reason for this is unknown at this time. ACKNOWLEDGMENT The authors acknowledge the sponsorship of this research project by the US Department of Energy Mining Industry of the Future Program. The authors also acknowledge their partnership with Sandia National Laboratories on this project. REFERENCES Stolarczyk, L. G. and S. S. Peng, 2003, Advanced Electromagnetic Wave Technologies for the Detection of Abandoned Mine Entries and Delineation of Barrier Pillars, Proc. Interactive Forum on Geophysical Technologies for Detecting Underground Coal Mine Voids, July 2003, Lexington, KY. Stolarczyk, L. G., S. S. Peng and Y. Luo, 2003, Imaging Ahead of Mining with Radio Imaging Method (RIM-IV) Instrumentation and Three-Dimensional Tomography Software, Proc. 22 nd Int l Conference on Ground Control in Mining, Morgantown, WV. Table 5. Summary of Quantitative Analysis Geological Factor Image Compiler Algorithm Data Shifting Thickness of Main Bench 1D A ART 50 ft to right Distance between Main Bench and Sandstone 3A B ART With or without 50-ft shift to right Number of Iterations 4, Sweeps 1, 2, 3 and 4 1 Undulation Factor 3A B ART 50 ft to right 1 Combination 3A B ART 50 ft to right 1 9