Field Instrumentation and Data Analysis of Ground Movement and Pillar Performance at the Maple Eagle Mine in Southern West Virginia

To promote the safety and health of U.S. mineworkers, researchers with the National Institute for Occupational Safety and Health (NIOSH) are currently involved in gathering additional field data from the nation’s underground coal mines. The purpose of this field study was to monitor ground movement and changes in pressure during mining where conditions include a thick parting in the coal seam. To accomplish this, three arrays of field instrumentation were installed in the wraparound bleeder of a room-and-pillar panel at the Maple Eagle mine located in southern West Virginia. Borehole pressure cells (BPCs) were used to monitor the change in pressure in pillars located adjacent to the gob. Roof extensometers were installed to measure roof sag at various horizons in the immediate roof, while rib extensometers were installed to measure displacement of the in-seam parting as mining progressed. Additionally, visual observations and manual measurements were taken during subsequent site visits. The repeatability of results, important from a scientific perspective, was accomplished by successfully obtaining field measurements from two nearly identical instrumentation sites. The data collected indicated that the front abutment extent at the edge of the panel was approximately 200 ft, corresponding to a distance of 9– 10 times the square root of the depth. Yielding of the slabbed pillar began when the pillar line was approximately 290 ft outby the instrumentation sites. This was followed by load shedding onto the abutments and the measurement of small amounts of roof sag in the No. 1 entry. Instrumentation data, as presented in this paper, can be used to better understand stress redistribution, pillar performance, and roof/rib displacements. Additionally, this data is suitable for assisting in the calibration of numerical models. Insight gained from applying these models can be used to make better engineering-based judgments for conditions that could potentially be encountered in the future.