Barcoded NanoTags for Real-Time Tracing Cuttings in Mud Logging

Abstract

Abstract Rock cuttings are often collected for lithology and petrophysical characterization during a drilling operation. The depth origin of the sampled cuttings could be determined by calculating the lag time required for the cuttings to travel from the bit to the surface, but traditional mud logging methods may give inaccuracies of ±10-20 feet in the depth correlation due to the shuffling and settling of cuttings as they travel with drilling fluid to the surface, especially for horizontal wells. Aramco researchers have developed a technology that pulse pumps a series of barcoded tags sequentially to label drill-cuttings when they are formed during drilling without adverse impact on the drilling operation in field, and field tests demonstrated that the depth-correlation uncertainty could significantly improve to about ±2 feet. However, this technology critically relies on the efficiencies of mud tracer materials and technology of rapid detection for real-time monitoring in mud logging. To enable the determination of cuttings at various depths and times, a number of mud tags are essentially needed. Towards achieving this goal, we have developed 6 series of novel tracer materials as mud tags and analytical methods for rapid, trace level detection of these tags. The new series of nano tracer materials (NanoTags) include CompTags, MagTags, PolyTags, FluorTags, CarbTags and FiberTags, in which unique compositions or optical properties as barcoded information are incorporated. The synthesized tracer materials have controllable compatibility with either water-based mud (WBM) or oil-based mud (OBM) and have been tested in simulated mud formulation and cutting samples. Stability tests demonstrated that the tracers are stable in simulated reservoir condition with high-salinity water and crude oil at elevated temperature (~95°C). These NanoTags in drilling muds can embedded into cuttings at a drilling bit and travel with the cuttings to surface, and then be identified by optical detection and other orthogonal analyses using various detection methods at nano-gram level in the cutting samples.