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By Hugo Melo

Fault Characterization and Modelling in the Deep Mill Level Zone (DMLZ) Mine

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The East Ertsberg Skarn System is a large skarn and porphyry deposit in Papua, Indonesia that formed between the northern contact of a large diorite intrusion and the southern flank of a regional synclinal-type fold within carbonate-rich sedimentary sequence. PT Freeport Indonesia is currently mining the fourth and deepest phase (1,500 m) of the Deep Mill Level Zone (DMLZ) mega skarn column, after depleting the upper sections of the orebody. The induced vertical stresses combined with the competent nature of the rock mass in the Ertsberg diorite intrusion present challenges for cave propagation and rock fragmentation, as compared to the exoskarn rock mass hosted in adjacent carbonates. The depth of the DMLZ creates a geologic condition where the rock mass is more competent. Joint and weak vein densities are low. Non-continuous, segmented, tight faults have reacted to high excavation stresses, focusing seismicity during the mine development and initial block caving. These challenges have pushed the team to keep enhancing the quality of data collection and modeling. Caving is currently being assisted through a comprehensive hydraulic fracturing program.

The mine is in a tectonic accretionary belt between the Australian and Pacific plates that formed a fold and thrust belt over the last 25 million years ago (Ma). Characterizing and modeling the faults in the DMLZ mine are one of the most critical tasks to support the mining operation, by providing detailed structure, vein and fracture frequency models as input for geotechnical analysis. The nature of structures within the 2.6 Ma diorite are distinguished from those in the older sediments. This paper presents the results of the study defined to better understand fault systems in the DMLZ. The objectives are to provide the most robust fault model and fault characterization matrix that will serve as input into the geomechanical design models as well as into fragmentation and caveability models.