Lithology-lndependent Gas Detection by Gradient-NMR Logging

Abstract

It has been shown that the Magnetic Resonance Imaging Log (MRIL) can detect hydrocarbon gases present in the near wellbore zone (approximately 10 cm from the borehole wall). By exploiting the T1 - and diffusion-weighting capabilities of this tool, mineralogy-independent water and hydrocarbon saturations can be determined in this zone. Gas and oil saturations are used to correct the reduction in apparent NMR porosity, an effect due to reductions in hydrogen index and incomplete recovery of magnetization polarization. The proposed method exploits the predictability of density, hydrogen index, T1 and diffusivity of the non-wetting phase from its bulk properties. Gas is always and oil is often non- wetting. The MRIL /C's multi-frequency capabilities are used to integrate changes in recovery time and/or echo spacing into a single logging pass. The resultant data streams are processed in the complex time-domain to extract signal components characteristic for hydrocarbons. Introduction Nuclear magnetic resonance (NMR) logging has the potential to become the measurement of choice for determining formation porosity. Unlike nuclear porosity logs, the NMR measurement is environmentally safe and is unaffected by variations in matrix mineralogy. A major barrier to using NMR alone for porosity determination has been the widespread belief that a near-wellbore NMR measurement cannot detect hydrocarbon gases. Akkurt, Vinegar, Tutunjian and Guillory of Shell have recently shown this belief to be erroneous. In their fundamental paper, these authors point out that NMR signals from gas protons are detectable and derive T1 relaxation and diffusion properties, of methane-dominated natural gas mixtures at typical reservoir conditions. The magnetic field gradient of NUMAR's Magnetic Resonance Imaging Log' (MRIL) enabled them to separate and to quantify water, oil and gas saturations based solely on NMR data. The present paper expands Akkurt et al.'s scheme by performing the entire detection procedure in the complex-valued time domain. At every depth and in real time, matched filters are computed based on reservoir temperature and pressure and on known probe properties. Filtering separates the oil and gas signals and submits only the brine component to T2 inversion for an estimate of irreducible water saturation. This scheme is advantageous in low-porosity formations, where low signal-to-noise ratios tend to broaden all T2 components. Corrections for hydrogen index (HI) and incomplete longitudinal recovery enable us to calculate a gas-filled porosity and to correct both apparent NMR porosity (MPHI) and free fluid index FFI, which are necessary to arrive at a valid estimate of formation permeability. The paper is organized as follows: First, we examine hardware requirements and limitations for valid T1-weighted measurements. Next, the temperature and density dependencies of hydrogen index and apparent T1 and T2 times of methane are given in parametric form. Optimum acquisition schemes for T1-weighted/diffusion-weighted T2 measurements are discussed. The construction of time-domain matched filters and their application to the complex-valued tool data are demonstrated. It is assumed that the reader is familiar with the MRIL architecture, as well as with Akkurt et al.'s paper. Hardware Requirements In order to separate signal contributions from different fluids, an NMR tool must be able to operate in a three-dimensional parameter space: T2 (transverse decay time), measured by a CPMG pulse-echo sequence; T1 (longitudinal polarization time), measured by variable saturation-recovery times; P. 325

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