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Abstract Formation grain size distribution is important in reservoir sand management, perforation, optimizing fracturing strategy, and predicting depositional and diagenetic facies and hydraulic units. This paper describes a new method of using acoustic velocities and NMR relaxation time spectrum to determine parameters of formation grain size distribution. Grain size distribution is often approximated by normal, log-normal, binary, or more general types of distribution, e.g., Weibull distribution. In most cases, however, it can be characterized by two numbers: mean grain size and sorting, which describe, respectively, the measures of the center and the spread of a grain size population. The influence of sorting on acoustic properties of porous media is well known; however, there is no direct relationship between acoustic properties and mean grain size. NMR T1 and T2 relaxation time spectra of wetting phase are directly related to the distribution of pore volume-to-surface ratio, which, in turn, depends on the mean grain size. On the other hand, there is no straightforward correlation between NMR relaxation time and sorting. Moreover, neither NMR nor acoustic data alone can resolve effects due to heterogeneity in mineralogy and heterogeneity in pore geometry (sorting, compaction, cementation, etc). The approach presented in this paper is based on the predictions of NMR T2 spectrum and acoustic velocities in numerical model rocks having different grain size distribution. Pore geometry of these model rocks is defined by geologic and mineralogical information about the formation. This information is supplied by a mineral reading from a logging tool, from drilling cuttings, or from prior knowledge based on core or logging data of a similar field. Based on the results of these predictions, we show that NMR relaxation time spectrum allows estimating mean grain size, and that compressional and shear acoustic velocities provide means to compute sorting parameter. The results are compared with the sandstone core measurements data and are found to be consistent with them. Introduction Determination of grain size distribution is important to sand management of unconsolidated formations [Oyeneyin et al., 2005; Nouri et al., 2006], for predicting depositional and diagenetic facies and hydraulic units [Altunbay et al., 1994], and for estimating penetration depth in perforation [Brooks et al., 1998]. Traditional methods of measuring grain size distribution include sieve analysis or laser particle size analysis for unconsolidated sediments or crushed rocks, and image analysis of thin sections for consolidated rocks. However, all these methods are laboratory analysis methods and require core samples, which are not readily available and may not be representative of the whole intervals of interest. Therefore, there is a need for a reliable technique to calculate grain size distribution of formation rocks from the downhole formation evaluation data. The idea of using NMR T1 or T2 relaxation time distribution to determine grain size is well known in the literature. Recently, we have developed an approach of utilizing NMR T2 spectrum to calculate grain size distribution based on pore scale modeling [Chen et al., 2007].
- Europe (0.94)
- Asia (0.68)
- North America > United States > Texas (0.46)
- Geology > Sedimentary Geology (1.00)
- Geology > Geological Subdiscipline (1.00)
- Geology > Mineral > Silicate (0.73)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.50)
Abstract We have developed a data processing method that allows a valid integration, in the time domain, of echo trains acquired in different field gradients, G, and different interecho times, TE. The combined echo train can be used to obtain clay bound water (CBW), bulk volume irreducible (BVI), and total porosity information with improved vertical resolution. The same data, in the uncombined form, are used for fluid property estimation. Thus, the data are used more economically. As an added benefit, the combined echo train allows the use of a single T2cutoff, consistent with the laboratory core-NMR derived T2cutoff. Although using a zero-gradient, laboratory core-NMR derived T2cutoff to "calibrate" NMR logs acquired in a gradient field is a common practice, the discrepancy cannot be ignored for NMR logs acquired with a large G·TE product. With the new method, this discrepancy is minimized. Field examples are provided to show the benefit with the new method. Introduction The new generation, multi-frequency NMR logging instruments, such as the Magnetic Resonance Explorer™? (MREX™) from Baker Atlas, are capable of acquiring data useful for characterizing both the formation rock properties (e.g., bound and movable fluids, porosity, and permeability) and reservoir fluid properties. However, these different properties often require an assortment of NMR acquisition parameters and sequences. High-resolution formation rock characteristics require acquisition schemes that generate repetitive echo trains to reduce the vertical stacking requirement. In contrast, fluid properties usually vary more slowly with depth than rock properties and require acquisition methods that can maximize the fluid contrasts, achievable with variable magnetic field gradients (G), interecho times (TE), and wait times (TW) in the acquisition scheme. Currently, multiple G, TE, and TW data are not combined in the time domain to obtain formation rock properties because echo trains having different G·TE cannot be simply stacked. Common practice is to log either multiple passes, each for a separate objective or a single, slow, comprehensive acquisition pass. Either way the data are not used economically. Baker Atla's global NMR logging service records reveal that a high percentage of NMR logging job requests are for formation rock property characterization. These properties include total and effective porosities, clay and capillary bound water volumes, movable fluid volume, and permeability. Light hydrocarbon typing and flushed-zone gas or oil saturations comprise the next largest group of logging job requests. There are also less commonly exploited techniques of NMR logging, such as those used in heavy oil formations, which have experienced some success in various geological areas worldwide. This global picture roughly reflects the relative robustness of the NMR logging techniques available to-date. Based on this assessment, we have developed a small-number of objective-oriented acquisition sequences that coincides with this global picture. These single-pass, comprehensive sequences all include an objective of formation rock property estimation.
Summary We develop a numerical algorithm to simulate nuclear magnetic resonance (NMR) measurements in the presence of constant magnetic field gradients. The algorithm is based on Monte Carlo conditional random walks in restricted and unrestricted space. Simulations can be performed of 3D porous media that include both arbitrary bimodal pore distributions and multiphase fluid saturations. The ability to account for the presence of a constant external magnetic field gradient allows us to replicate actual well-logging conditions that include the effect of Carr-Purcell-Meiboom-Gill (CPMG) pulse sequences at a microscopic level. This is accomplished by simulating ideal pulse-acquisition techniques that include multiple interecho times (TE) similar to those currently used by the well-logging industry. Benchmark examples are presented to validate the accuracy and internal consistency of our algorithm against previously published results for the case of a null magnetic field gradient. Validation examples also are presented against actual NMR measurements performed on core samples of carbonate rock formations. Interpretation work is focused on the petrophysical assessment of both partial oil/water saturations and pore structures exhibiting diffusive coupling. Simulation examples are designed to quantify whether the inclusion of diffusion under a magnetic field gradient can improve the interpretation of multiphase fluid saturations when diffusion coupling is significant. The simulation algorithm sheds light on new NMR data-acquisition strategies that could be used to improve the detection and quantification of fluid types, complex fluid saturations, and complex pore geometries. Introduction The presence of diffusion pore coupling in carbonate rocks (mainly grainstones) challenges conventional NMR interpretation techniques. Although pore-coupling phenomena are commonplace in the majority of rock pore systems, they become relevant to assess NMR measurements when the following three conditions are met:microporosity regions are present within the grains; micropores are well-connected (not cemented) to outer macroporous regions exhibiting low surface-to-volume ratios, thereby allowing fluid diffusion between both pore scales; and rock surface relaxivity is low enough to prevent the decay of proton magnetization within the macroporosity before protons can enter the microporous regions. In addition, fluid diffusivity must be sufficiently large for diffusion coupling to be significant within the time scale of NMR measurements. This is usually the case only for water and light hydrocarbons. As a result, fluid magnetization will be exchanged between micro- and macropore regions, and no obvious relationship will exist between NMR transverse relaxation (T2) distribution and pore-size distribution. Fig. 1 illustrates conditions (a) and (b), described previously, with an example of scanning electron microscope (SEM) images of a carbonate rock exhibiting diffusion coupling. Varying TE is a common NMR data-acquisition technique used for in-situ reservoir fluid identification. However, in the case of NMR measurements performed in carbonate rocks, there are no published reports dealing with the impact of diffusion coupling on hydrocarbon typing and quantification using multiple-TE logging techniques. The objectives of this paper are two fold:to develop a simulation algorithm capable of reproducing NMR measurements in complex pore geometries under a variety of experimental conditions and (in particular) under the influence of a constant magnetic field gradient, and to provide simulation examples that will help assess the validity of fluid phase discrimination using multi-TE measurements in porous media exhibiting diffusion coupling. In the past, numerical models of NMR decay were proposed based on periodic bimodal packs of spheres that accounted for surface relaxation effects. We have reproduced and extended Ramakrishnan et al.'s Monte Carlo algorithm to account for the effect of an external constant magnetic field gradient of the type enforced by modern NMR tools, and in the presence of a nonwetting phase. The first part of this paper introduces the Monte Carlo simulation algorithm applicable to a bimodal pack of spheres in the presence of a constant magnetic field gradient. A subsequent section describes examples of numerical simulation that illustrate the versatility of the algorithm. Finally, we derive and interpret simulation examples intended to address specific issues of fluid discrimination using multiple interecho times in the presence of diffusion coupling. We address four specific cases of NMR T2 distributions (two unimodal and two bimodal) by modeling several possible combinations of pore structure, diffusion coupling, and fluid distribution. These case studies were designed so that different pore configurations created identical NMR signals at low values of TE but exhibited differences at high values of TE. Model for the Simulation of NMR Decay The algorithm developed to numerically simulate NMR magnetization decay in carbonate rocks makes use of conditional Monte Carlo random walks. It is based on the algorithm described by Ramakrishnan et al., further generalized to include microscopic diffusion effects in the presence of a constant magnetic field gradient. The assumption of a constant gradient across the zone probed by NMR tools is generally an accurate approximation in the presence of small contrasts of magnetic susceptibility (i.e., in the absence of paramagnetic materials). Porous media can include micro- and macroporous regions (grainstone model) to form a bimodal pore distribution, or they can exhibit a single pore size with solid grains (wackestone model).
ABSTRACT Experience has demonstrated that NMR well logging is capable of delivering a spectrum of rock and reservoir fluid properties that are essential to formation and reservoir evaluation. However, these capabilities are not always fully realized because the NMR data acquisition program requires optimization by the logging engineer. The lack of a straightforward link between NMR-specific parameters and the desired rock and fluid properties contributes to the difficulties. Furthermore, to ensure high quality results, it is desirable to acquire all NMR data simultaneously in a single logging pass. To pack all of the NMR pulse sequences in one pass requires optimal design of the NMR acquisition program. With the MR Explorer logging system, there is no need to customize the NMR acquisition program based on borehole loading, borehole size, or logging speed. The number of frequencies and NMR logging parameters are automatically chosen by the acquisition scheme, and the logging engineer is not required to make down-hole adjustments as was needed with earlier generation NMR logging tools. Thus, it is much less demanding on job planning and much less prone to operator errors. This process enables engineers and petrophysicists to focus on defining logging objectives rather than struggling with unfamiliar NMR acquisition parameters. The result is improved well-site efficiency and fit-for-purpose NMR logging acquisitions. The MR Explorer tool delivers all of the standard outputs associated with NMR logging, including reservoir fluid typing and quantification data. The logs from several test wells and oil wells confirm the performance of the new tool and the value of the new logging methods.
- North America > United States > Texas (0.28)
- Europe > United Kingdom > England (0.28)
Abstract We develop a numerical algorithm to simulate nuclear magnetic resonance (NMR) measurements in the presence of constant magnetic field gradients. The algorithm is based on Monte Carlo conditional random walks in restricted and unrestricted space. Simulations can be performed of three-dimensional (3D) porous media that include both arbitrary bimodal pore distributions and multi-phase fluid saturations. The ability to account for the presence of a constant external magnetic field gradient allows us to replicate actual well logging conditions that include the effect of CMPG pulse sequences at a microscopic level. This is accomplished by simulating pulse acquisition techniques that include multiple inter-echo times (TE) similar to those currently used by the well-logging industry. Benchmark examples are presented to validate the accuracy and internal consistency of our algorithm against previously published results for the case of a null magnetic field gradient. Validation examples are also presented against actual NMR measurements performed on core samples of carbonate rock formations. Interpretation work is focused to the petrophysical assessment of both partial oil/water saturations and pore structures exhibiting hydraulic coupling. Simulation examples are designed to quantify whether the inclusion of diffusion under a magnetic field gradient can improve the interpretation of multi-phase fluid saturations when hydraulic coupling is significant. The simulation algorithm sheds light to new NMR data acquisition strategies that could be used to improve the detection and quantification of (a) fluid types, (b) complex fluid saturations, and (c) complex pore geometries. Introduction Presence of hydraulic (or diffusion) pore coupling in carbonate rocks (mainly grainstones) challenges conventional NMR interpretation techniques. Although pore coupling phenomena are commonplace in the majority of rock pore systems, they become relevant to assess NMR measurements when the following three conditions are met:micro-porosity regions are present within the grains, micro-pores are hydraulically well connected (not cemented) to outer macro-porous regions exhibiting low surface-to-volume ratios, and rock surface relaxivity is low enough to prevent decay of proton magnetization within the macro-porosity before protons can enter the micro-porous regions. In addition, fluid diffusivity must be sufficiently large in order for hydraulic coupling to be significant within the time scale of NMR measurements. This is usually the case only for water and light hydrocarbons. As a result, fluid magnetization will be exchanged between micro- and macro-pore regions, and no obvious relationship will exist between NMR transverse relaxation (T2) distribution and pore-size distribution. Figure 1 illustrates conditions (a) and (b) described above with an example of scanning electron microscope (SEM) images of a carbonate rock exhibiting hydraulic coupling. Varying inter-echo times (TE) is a common NMR data acquisition technique used for in-situ reservoir fluid identification. However, in the case of NMR measurements performed in carbonate rocks, there exist no published reports dealing with the impact of diffusion coupling on hydrocarbon typing and quantification using multiple-TE logging techniques. The objectives of this paper are twofold:to develop a simulation algorithm capable of reproducing NMR measurements in complex pore geometries under a variety of experimental conditions and, in particular, under the influence of a constant magnetic field gradient, and to provide simulation examples that will help assess the validity of fluid phase discrimination using multi-TE measurements in porous media exhibiting hydraulic coupling.
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Electromagnetic Surveying > Electromagnetic Acquisition (0.41)
ABSTRACT Nuclear Magnetic Resonance (NMR) is the only logging technique available to estimate pore-size distributions. However, quantitative interpretation of NMR data can become uncertain in carbonate rocks because of unaccounted diffusive coupling between existing pore scales. The objective of this study is to assess the relative importance of diffusive coupling and temperature using practical examples encountered in the interpretation of NMR data. The core of our work is based on the analysis of experimental NMR measurements and their comparison with numerical simulation results. Our numerical simulation algorithm consists of Monte-Carlo random walks in three dimensions and was specifically designed to account for two-phase fluid saturations in the presence of a bimodal poresize distribution. We present numerical simulation results that reproduce MR/L experimental data acquired in carbonate rocks exhibiting bimodal pore-size distributions and two-phase fluid saturations. Simple interpretation models are derived to include NMR coupling effects by way of cross-interactions between the fluids borne within the different types of pores. Such models have been subsequently used to assess the importance of diffusion coupling. Experimental data acquired from rock core samples was also used to assess the influence of temperature on the estimation of movable fluids volumes otherwise determined assuming a constant formation T2cutoff. It is shown that temperature has moderate effect on T2 distribution, T2~, off, and BVI determination. The diffusive coupling effect is more significant on mapping I"2 distribution to pore size distribution than on the determination of BVI.
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
This paper was prepared for presentation at the 1999 SPE Annual Technical Conference and Exhibition held in Houston, Texas, 3–6 October 1999.
ABSTRACT Irreducible water saturation (Swi) and bulk volume irreducible (BVI) water from nuclear magnetic resonance logging are not directly measured quantities but are derived from the T2 distribution and the effective porosity. Thus, they are dependent on models and the associated parameter used in the interpretation of the T2 distribution data. It has been standard practice to use a T2 cutoff value to partition the T2 spectrum into irreducible and moveable fluids. This assumes that small pores are filled with irreducible water and that large pores contain moveable fluids (either hydrocarbons or water). Such an approach brings forth arguments both from scientific considerations and from the practical applications point of view. Scientifically, it is also possible that pores are incompletely drained; a film model may be more suitable for describing BIKE. In practice, a sharp T2 cutoff may result in very small or "zero" BVI, if either the T2 cutoff value or the estimated T2 distribution is inaccurate. Such a phenomenon has been observed on logs from the Gulf of San Jorge Basin, Argentina and is known also to occur in formations elsewhere. We investigated the relationship between T2 cutoff and the film model and, for simple pore geometric models, derived transcendental equations for predicting film model BVI weighting functions based on T2 cutoff values. We found that the BVI weight functions are not very pore geometry sensitive and based on that, a procedure to compute a generic BYE weighting function is derived. The method is illustrated with core samples from the Gulf of San Jorge Basin and has been applied routinely since 1995 to several hundred NMR well logs. In addition, we used a second approach to estimate BVI weighting functions by forming the ratio of individual incremental porosity bins of the 100% saturated and desaturated core NIvIR T2 distributions. This approach appears more reasonable for cases when the short T2 bin porosities in the desaturated T2 distribution exceed the corresponding bin porosities in T2 distribution of the fully saturated data. Both approaches work well with San Jorge Basin data and are easy to use.