In this paper, we present a new surface logging technology, named the Automated Mud Logging System (AMLS), which is a cost-effective alternative to advanced wireline logging required to identify producible oil in tight rocks.

AMLS provides characterization of drill cuttings samples at the well site. Current version of the system (AMLS ver 1.0) includes a Natural Gamma-ray Spectrometer (NGS) and Nuclear Magnetic Resonace (NMR) relaxometer, with an automated sample feeding system which can be installed in a mud logging unit to perform sample analysis while drilling. The sensitivity of NGS and NMR measurements to sample volume avoids time consuming and labor intensive sample preparation required by other geological material characterization methods (e.g. X-ray diffraction, X-ray fluorescence, etc.) which are surface sensitive. The ability of NGS and NMR to characterize "as received" cuttings allows for the automation of data acquisition and minimizes the operational expenses.

Results from a field trial of AMLS on a vertical well, drilled through tight formation at a rate of penetration (ROP) of approx. 120 ft/hour are also presented. The uranium (U) concentration curve from cuttings, acquired by the AMLS ver 1.0, compares favorably with that acquired by a wireline tool. This demonstrates the robustness of the developed system to characterize drill cuttings for formation evaluation. The main challenge in cuttings analysis is ensuring efficient mud logging operations at the well site during fast drilling (e.g. sampling cuttings every 5 ft in depth with a ROP of 100-120 ft/hr)

The presented results demonstrate the feasibility of converting mud logging from a source of qualitative information about the subsurface into a source of quantitative information comparable to the information delivered by wireline or LWD logging but acquired at much lower cost and operational risk. The addition of other components to AMLS such as automated sample catcher and Neutron Induced Gamma-ray Spectroscopy (NIGS) measurement system should make this mud logging system even more valuable source of subsurface information. Another enhancement of the data acquired by AMLS can originate from properly acquired advanced mud gas logs. An example of the application of data acquired by NGS node of AMLS ver 1.0 and mass spectroscopy-based mud gas logging system to identify intervals containing producible oil in a tight rock formation in West Texas, is presented.

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