Fluid typing with NMR logging

Hydrocarbon typing and prediction of fluid properties by nuclear magnetic resonance (NMR) logs is predicated on reliable laboratory correlations between NMR measurements (i.e., relaxation times and diffusion) and fluid properties, for example:

·         Specific gravity

·         Viscosity

·         Gas/oil ratio (GOR)

Early studies were limited to investigations at ambient conditions; however, using the standard correlations derived from these studies may result in seriously underestimating viscosity. More-recent studies have expanded these correlations to oils and mud filtrates at reservoir conditions.

Characterizing fluid properties

The NMR T2-porosity relationship in which T2 is a function of pore size (i.e., S/V ratio, see Eq.1) holds for water-saturated rocks. The presence of hydrocarbons in water-wet rocks alters the T2 distribution, thus affecting the porosity interpretation. Despite the variability in the NMR properties of fluids, the locations of signals from different types of fluids in the T2 distribution can often be predicted or, if measured data are available, identified (Fig. 1).

Fig. 1 – NMR-oil typing. The position and spread of the oil component in the T2 distribution depends on oil viscosity and formation wettability. Oil typing is easiest in water-wet formations because of the moderate breadth and distinct positions of the different oil components in the T2 distribution. Oil typing is most difficult in mixed-wet formations because the oil and water components are broad and overlap one another.

NMR logging uses specialized Carr-Meiboom-Purcell-Gill (CMPG) pulse-acquisition sequences to exploit these differences in pore-fluid NMR properties to achieve specific objectives. The CMPG parameters—wait time (TW), echo spacing (TE), the number of echoes (NE), and the number of sequence repetitions—are selected to take advantage of the wide variation in NMR fluid properties (Fig. 2) for estimating total porosity and for hydrocarbon typing. Table 1 illustrates the range of NMR-related properties of fluids for Gulf of Mexico sandstones, for example. Table 2 lists variations in CMPG pulse sequences for different objectives using time-domain analysis (TDA) and Enhanced Diffusion Method (EDM). The multifrequency tools now in service permit the simultaneous acquisition of multiple measurements on the same rock volume using different acquisition sequences during the same logging run. The general approach is to log in a mode that allows gathering the full spectrum of data. Specialized applications, including some direct fluid-identification methods, involve customized-acquisition sequences that require slower logging and acquisition of more echoes.

Fig. 2– Typical NMR properties for pore fluids. Differences in these properties between fluids are exploited by methods that use specific acquisition sequences for hydrocarbon typing buy use of T1 or diffusion-weighting mechanisms.

Table 2

Determination of the appropriate interpretation method is largely based on the estimated viscosity of the anticipated hydrocarbons (see Fig. 3). These methods will be explained in the following paragraphs.

Fig.3 – Graph indicating the current viscosity limits for NMR-interpretation techniques. The resistivity-density technique is limited to gas reservoirs, and the SSM method has been effectively replaced by the newer DSM method. The y-axis is the relaxation time.

Selection of the appropriate acquisition sequence and the choice of acquisition parameters depend on the logging objectives and are part of prejob planning. This process considers several factors regarding the anticipated rock and pore-fluid properties. For example, for characterizing large pores (clastics), clean formations, carbonates, and light oil—all of which are associated with long-T2 values[4]—a large number of echoes should be acquired, and a longTW should be used. However, more echoes and longer TW may require reduced logging speeds. In contrast, characterization of small pores (i.e., low permeability), shaly formations, low porosity, and BVI determination involves the short T2 component of the NMR-porosity spectrum and often it can be accomplished using fewer echoes and shorter TW, which may allow normal logging speeds.

Fluid-typing methods fall into two broad categories depending on the NMR properties that are being exploited:

T1-weighting mechanisms take advantage of differences in fluid T1 values

Diffusion-weighted mechanisms make use of the diffusion-constant differences between oil and water

There are two general types, or sets, of CMPG acquisitions that are associated with each mechanism:

Dual TW

Dual TE

These two sets cover the range of major fluid-typing objectives; some interpretation techniques can use one or the other, or both. Each serves specific purposes and is optimized to provide data for specialized analysis programs. In general terms, each consists of at least two echo-train acquisitions in which one or more parameters are varied. The total, or the difference between the echo-train signals, provides an estimate or indicator of porosity, light hydrocarbons, or oil ('Fig. 4).

Fig. 4– CPMG acquisition types used for hydrocarbon typing: (a) a T1-weighted method is used to differentiate hydrocarbons from water, and (b) a diffusivity-weighted method is used to differentiate viscous oil from water or to differentiate gas from liquids.

Advanced hydrocarbon-typing objectives can involve customized-acquisition sequences[5] that are run at reduced logging speeds or even in stationary mode.

T1-weighted mechanism (dual-TW acquisition)

The dual-TW acquisition method is used primarily to identify and quantify light hydrocarbons (gas and light oil) by separating them from the water signal through T1 weighting. The dual-TW acquisition can also provide the standard-T2 acquisition dataset for determination of spectral NMR porosity, permeability, and productivity (mobile fluids). The TE is kept the same in both echo-train acquisitions (0.9 or 1.2 ms), and a short TW (1 second) and long TW (8 seconds) are used. The water signal is contained in both acquisitions, but because of the light hydrocarbons (which have long T1 values), the signal is suppressed in the acquisition using the short TW. Thus, the presence of a signal in the difference of the measurements (differential spectrum) is considered a strong indicator of gas or light oils[6] (Fig.5).

Fig.5 – Methods using T1-weighting for hydrocarbon typing: (a) in TDA, T2 echo-train subtraction takes place in the time domain, and (b) in the differential-spectrum method (DSM), T2 echo-train subtraction takes place in the T2 domain.

Fluid volumes can be quantified by integrating the difference into T2 spectra and correcting for the polarization difference between long and short wait times. Fluid typing and quantification are performed through the differential-spectrum (DSM) method and the TDA method. Two conditions must be met to ensure successful DSM interpretation:

T1 contrast between the hydrocarbon and brine phases (i.e., a water-wet formation containing light hydrocarbons)

T2 contrast between the gas and oil phases

DSM assumes that the hydrocarbon phases relax uniexponentially. DSM is commonly used for: (1) hydrocarbon typing in shaly sands, where the the neutron-density crossover may be suppressed because of the high amount of clay minerals in the rock[7][8] to confirm the presence of light oil in fine-grained rock, and (2) for gas detection in the presence of OBM invasion.[9] Ideally, DSM can be used to compensate for the hydrocarbon effects on NMR measurements and thereby enable correction of NMR total porosity and NMR effective porosity; however, because of S/N requirements, TDA is the preferred technique for correcting NMR logs.

In contrast to the DSM approach, the TDA technique works directly with the echo-decay data (i.e., in the time domain rather than the T2 domain; see Fig.6). The measured long- and short-wait-time decay trains are subtracted into an echo difference that indicates the presence of a long-T2 component (usually a hydrocarbon). By working in the time domain, when the T2 inversion is performed, only the hydrocarbon T2 component will be present.

Fig.6 – Example of TDA. Track 1 shows the pore volumes for gas(red), OBM filtrate and/or native oil (green), movable water (dark blue), and capillary-bound water (light blue) obtained from TDA quantitative analysis using an MRIL data set. Tracks 2 and 3 show the T2 and T1 values, respectively, of gas and light oil calculated through TDA. The lower part of Track 2 shows the oil/water and gas/oil contacts, while the upper part of the track indicates the presence of gas and oil.

TDA—an outgrowth of the DSM technique—is based on the fact that different fluids have different rates of polarization (i.e., different T1 relaxation times).[10] TDA provides the following results:

Fluid types in the flushed zone

Corrected NMR porosity in gas reservoirs

Corrected NMR porosity in light oils

Complete fluid-saturation analysis in the flushed zone, using only NMR data

The TDA technique is a more robust method than DSM, in part because it provides better corrections for underpolarized hydrogen and HI effects[11] (Figs.6 and 7).

Fig.7 – Log examples showing the results of DSM and TDA analysis. Light hydrocarbons can be identified through the subtraction of echo trains obtained at two polarization times. Track 4 displays the differential spectrum obtained from the subtraction of the two separate T2 distributions derived from echo trains acquired with short- (TWL) times, TWS = 1 second and TWL = 8 seconds. The water signals in each completely cancel, while hydrocarbon signals only partially cancel and remain when the two T2 distributions are subtracted from one another. Track 5 displays the TDA results. TDA is performed in time domain (as opposed to T2 domain), and can quantify up to three phases (gas, light oil, and water; gas and water; or light oil and water).

Several factors inherent in the dual-TW acquisition require reduced logging speeds:

·         To achieve full polarization (long TW) in one acquisition channel

·         To acquire the small signal amplitudes associated with the short

TW values in another other channel

·         To meet the requirement for acceptable S/N levels

A new triple-wait-time method addresses these issues and also allows T1 acquisition.