IMPROVED FLUID TYPING WITH NMR: BETTER FIELD DEVELOPMENT PLANNING IN DEEPWATER NIGERIA

Transcription

1 IMPROVED FLUID TYPING WITH NMR: BETTER FIELD DEVELOPMENT PLANNING IN DEEPWATER NIGERIA Russell W. Spears 1 and Souvick Saha 2 1 ExxonMobil Development Company, Houston, Texas 2 Schlumberger, Lagos, Nigeria FFF Copyright 2005, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. This paper was prepared for presentation at the SPWLA 46 th Annual Logging Symposium held in New Orleans, Louisiana, United States, June 26-29, ABSTRACT In deepwater Nigeria, accurate fluid characterization is often challenging, and the results are sometimes unexpected. Several cases of isolated sand bodies containing both water and oil within the main oil column have been documented. In other examples, variation from light oil to gas within some sands is often very subtle and commonly goes undetected using conventional formation pressure gradient analyses. Both cases tend to increase the level of reservoir complexity and make accurate fluid characterization increasingly difficult. In an expensive deepwater exploration or appraisal scenario, accurate fluid characterization is critical for efficient and effective planning of reservoir and field development. Accurate and comprehensive characterization of fluid types can be made in deepwater Nigeria wells if nuclear magnetic resonance (NMR) and NMR fluid typing is applied before formation pressure data acquisition. The NMR fluid-typing method exploits the fact that the molecular diffusion coefficients of brine, oil, and gas molecules typically have values that are well separated from one another. Thus, the diffusion attenuation of a suite of measured NMR signals contains sufficient information to allow differentiation of brine, oil, and gas. NMR fluid typing brings new insight into formation fluid characterization and helps to optimize formation pressure and sampling acquisition. NMR fluid-typing data were acquired in two deepwater (Nigeria) wells. In one case study, an average formation pressure gradient analysis could not accurately identify water-bearing sands in the well while the NMR fluid- typing technique unambiguously identified the presence of water. Fluid sampling in the same interval post-nmr fluid typing has shown that the formation is indeed water bearing. The second case was used to determine whether the main sand of interest contains light oil or condensate or gas. NMR Fluid 1 typing suggested the presence of volatile oil with a high gas/oil ratio (GOR), while pressure gradient analysis indicated only the presence of gas. Fluid sampling in the same interval showed this particular formation to indeed be a gas condensate reservoir. The ability to ascertain reservoir quality and fluid type information with NMR is emerging as a very valuable technology in deepwater Nigeria developments. By using the NMR fluid-typing technique, uncertainty in these developments has been significantly reduced. Without this technique, interpreting fluid types in these examples would have been totally different. This, in turn, has directly impacted decisions and conclusions made about the field that will help in future geological modeling and depletion planning. INTRODUCTION Field location and background: The Erha field on OPL 209, deepwater Nigeria (Fig. 1), is located approximately 60 miles offshore Nigeria in roughly 1,100 m of water. In 1999, the field was discovered to contain oil and gas. Three appraisal wells were subsequently drilled and two well tests confirmed economic rates. A 24-well development was planned, and as of Spring 2005, 10 wells have been drilled and 3 completed. The field is a structural trap set up by a shale-cored anticline plunging north-northwest. Structural relief is provided by a series of normal faults that are confined to the crest of the main structure and extend into the eastern flank of the field. All of the faults are of relatively small offset, with most faults being less than 50 m. The productive section in Erha is comprised of middle Miocene turbidite sands. The environment of deposition is confined slope channel complexes with sands comprised of interbedded sands and shales of moderate-to-high porosity (18 26%). The reservoir sands in Erha are predominately deepwater turbidites ranging from Ta to Te facies (Fig. 2; Bouma, 1962)

2 with minor amounts of R and S beds (tractional) and sandy debrites scattered through the section. The Ta turbidite sands are by far the best reservoir facies within the section. These intervals are diagnostically very clean and very well sorted. Hence, the Ta turbidite sands exhibit the most uniform grain size distribution of any of the other facies in the section. In turn, the Ta turbidites exhibit the best porosity and permeability of any sands in the Erha productive section due to these excellent reservoir properties. R and S tractional beds are slightly poorer quality reservoir facies relative to the Ta turbidites. These beds typically contain angular rip-up clasts due to erosion during deposition and are usually found lining large channel bases. Shale rip-up clasts and poor sorting oftentimes reduce porosities and permeabilities dramatically as compared to the Ta turbidites. R and S beds are usually identified from openhole logs by higher resistivities and lower log porosities than other higher-quality Ta turbidite intervals. The sandy debrites found within the productive section in Erha usually have diagnostically low permeability resulting from elevated bound water content due to grain size variations or increased clay content. Sandy debrite intervals have been characterized in Erha cores as chaotic in nature with poor reservoir quality. Log responses in the sandy debrite intervals vary only slightly from the cleaner, higher-quality Ta turbidites. The sandy debrites are usually identified by a slightly elevated gamma ray response and slightly lower resistivity than the Ta turbidites associated with increased silt and clay (bound water). Note that the sandy debrites have been found to exhibit approximately 50% of the permeability of cleaner Ta turbidite sands through numerous well tests. Tb and Tc turbidites comprise the remaining section considered as reservoir material in Erha. The Tb and Tc facies are most commonly associated with thin-sand laminae that are usually interbedded with shales of considerable thickness and define classic marginal or thin beds intervals. These facies are often poorly resolved using openhole logs, but they are an important consideration in properly understanding both field inplace reserve volumes and dynamic production characteristics. Formation evaluation program for Erha development wells: The formation evaluation program for the exploration, appraisal, and development wells in Erha have included the use of both wireline and loggingwhile-drilling (LWD) technologies. Typically, gamma ray, compensated neutron, formation density, and 2 resistivity logs are acquired on LWD. These data have been used for basic petrophysical interpretations to compute porosity and saturations. NMR data were also acquired with wireline in most of the wells when operational conditions favored its use. These data are heavily relied upon for estimating reservoir quality as well as obtaining reliable fluid type information. The fluid-type information acquired from NMR data has become increasingly important in extremely costprohibitive environments such as deepwater offshore Nigeria due to the limited time investment in acquiring such information. Moreover, formation pressure data were acquired and fluid sampling was performed to have definitive answers on fluid characterization. Conventional core samples have been acquired in two appraisal wells and two development wells in Erha. Core samples are limited to the oil- and water-bearing intervals only. The conventional cores acquired in the appraisal wells utilized water-based mud, while the development well utilized oil-base mud. Different reservoir intervals and many different lithofacies types are represented in the conventional core record and have allowed for some calibration of the openhole log data to facies and fluid types. FLUID TYPING CHALLENGES IN DEEPWATER OFFSHORE NIGERIA Historically, detecting major differences in fluid type within the reservoirs in Erha has been handled, at a first pass, by using the standard openhole log suites, such as gamma ray, bulk density, neutron porosity, and resistivity. These measurements have proven to be very useful and accurate when confirming fluid type changes in clean, thick sands, but their use can be problematic when attempting to determine subtle differences in fluid type within intervals that exhibit variations in GOR, water saturation, or oil specific gravity. When standard openhole logs cannot conclusively answer questions and uncertainties regarding fluid types in complex scenarios, the formation pressure tester (FT) is almost always employed on wireline to make fine-scale pressure gradient and fluid sampling measurements. This avenue is inherently more accurate than standard open hole logs in determining subtle changes in fluid type or fluid characteristics. This technology requires large amounts of time for completing pressure testing stations because of long tool pump-out times that relate directly to large costs in rig time. Other problems commonly experienced by relying heavily on FT tools to obtain reliable fluid type information downhole are: finite limits in the number of samples that can be taken

3 during a single tool run (usually limited to 6 pressurevolume-temperature samples), tool mechanical problems (such as probe or flowline plugging) and sample drilling mud contamination. In the deepwater of Nigeria, service companies have aided operators in dealing with contamination problems and sample bottle limits by implementing on-board gas chromatograph or optical fluid monitoring devices. These devices have recently been employed to monitor sample contamination levels in real-time and provide preliminary indications of fluid type as fluid is drawn through the tool during sampling. In Erha, sometimes, the downhole fluid analyzing technology faces problem when contamination levels cannot be lowered enough via long pump-through times to capture usable samples for testing. In Erha gas, oil and water have been found unexpectedly within different portions of the reservoir. Petrophysical complexities of the formations in which these unexpected fluid types are being found (high GOR oil, gas, condensate) have created the need for a new and accurate fluid characterization method. Employing the NMR tool to obtain reliable and accurate fluid type information has recently filled this niche. Use of the NMR tool in this fashion has led to a cost effective and accurate fluid type identification method that can obtain fluid type information in multiple intervals on a single run. NMR AND NMR FLUID TECHNIQUE NMR logging tools provide unique petrophysical information not available from other well logging measurements. In particular, the benefits are: a) lithology-independent porosity measurements, b) rock quality (free and bound fluid porosity) information, and c) continuous permeability estimates. In recent years, the addition of a fluid typing/characterization technique with NMR logging has provided the petrophysical community with an important additional use of the NMR tool in the quest to reduce subsurface uncertainties. The detailed discussion of principles of NMR and NMR fluid technique is beyond the scope of this paper; however, these fundamentals have been extensively published in the literature and books on NMR well logging tools and NMR well logging methods and principles (Allen et al., 1997; Coates et al., 1999). Only the NMR principles that are applicable to deepwater Nigeria applications will be discussed in this paper. The first step in using the NMR experiment is to magnetize the formation fluids through applying a static magnetic field. The hydrogen nuclei contained in the oil, gas, and brine filling the pore spaces of rocks behave like microscopic magnets. The magnetic moments of the hydrogen nuclei align themselves along the direction of the applied magnetic field and create a net magnetization or polarization in the formation. The time required to align the hydrogen nuclei along the direction of the applied magnetic field, referred to as the longitudinal direction, is characterized by a longitudinal relaxation time, and typically denoted by an industry standard abbreviation of T1. Following the polarization time, a train of radio frequency (RF) pulses is applied. Between the RF pulses, the NMR signal is recorded using the same antenna used to transmit the pulses. The NMR signal observed between each pair of consecutive pulses is often called an echo. In a typical NMR measurement, several thousand echoes are acquired over a period of one second. The echo amplitudes are proportional to the net magnetization in the transverse plane (transverse to the static magnetic field), which decays during the course of the measurement. The rate of decay of the NMR signal can be described by distribution of decay times, T2s, which are referred to as transverse relaxation times. The transverse relaxation time is the component that provides useful information concerning the fluids and their environment. It is customary to fit the measured NMR signals to a sum of 30 decaying single-exponential signals, each with amplitude and associated decay time T2. The fitting procedure is achieved by mathematical inversion that results a plot of amplitude versus T2, which is known as a T2 distribution (Fig. 3). T2 distributions provide useful information because the area under the T2 distribution is proportional to the total porosity of the formation being measured. Also, in water-saturated rocks, the T2 distributions can be qualitatively related to pore-size distributions (Coates et al., 1999). By defining appropriate T2 cutoffs, the T2 distribution can be partitioned into bound water and free water. Permeability can then be estimated using a transform based upon total porosity and bound and free fluid proportion. Thus, based on this T2 distribution, an assessment of rock quality and permeability can be made. However, the presence of hydrocarbons such as crude oils and gas adds considerable complexity to the NMR signal. For bulk crude oils, the T2 distribution usually reflects the molecular composition of the oil. Each T2 in the distribution is inversely proportional to a FFF 3

4 microscopic constituent viscosity of a particular constituent molecule (Freedman et al., 2001). In partially saturated rocks, the brine and oil T2 distributions typically overlap. In this overlap, measured T2 distributions cannot always be used to distinguish oil from brine signals. The same is also true for T1 distributions. Fortunately, the molecular diffusion coefficients of oil, gas, and brine often differ significantly and this difference can therefore be used to separate the NMR signals for each of the three fluids. Molecular diffusion describes the random thermal motion of molecules, and the molecular diffusion constant is the mean square distance that the molecule will move per unit of time. The diffusion of gas and water molecules can be described by a single molecular diffusion constant (Kleinberg and Vinegar, 1996). Crude oils, on the other hand, have distributions of molecular diffusion coefficients that reflect the diversity of molecular sizes. complex data in an understandable format, such as the D-T2 map (Fig. 4). Just as T2 distributions provide interpretable representations of single-measurement NMR data, D-T2 maps provide unbiased representations of multi-measurement data suites. An overlay of the theoretical responses of the three most commonly encountered fluids (i.e., water, oil, and gas) aids in fluid typing using this presentation. APPLICATION OF NMR FLUID TECHNIQUE (CASE STUDIES) NMR and NMR fluid techniques are now routinely applied in deepwater Nigeria exploration and development wells. Two case studies of NMR fluid typing are presented that will exemplify the benefits of this technique. Prior to the NMR fluid typing technique (station measurement), 1 reservoir quality has historically been assessed with the NMR log. Methane and ethane are relatively mobile in the gas phase and have molecular diffusion coefficients (D) that are typically an order of magnitude greater than those of water molecules. In contrast, intermediate- to high-viscosity crude oils have much smaller molecular diffusion coefficients than those of water. With a specially designed suite of NMR signals that are sensitive to diffusion, contrasts in the molecular diffusion coefficients of formation fluids are utilized for distinguishing oil, water, and gas. Having established the concept of differentiating oil, gas, and water by diffusion, it is appropriate to address how diffusion measurements can be achieved by using the NMR tool. In fluid-filled rocks, the bulk and surface relaxation rates are independent of the spacing (TE) of the RF pulses; whereas, the diffusion attenuation rate is proportional to the product D TE 2, where D is the molecular diffusion constant of the fluid molecule. By acquiring suites of measurements with different pulse spacings, the signals from oil, gas, and brine in the formation are attenuated at different rates because of the differences in their molecular diffusion coefficients. This is the basis for the NMR fluid measurement; multi-fluid relaxation models and associated inversion techniques for suites of diffusionencoded data have been developed for determining oil, gas, and brine saturations (Slijkerman et al., 1999; Freedman et al., 2001). A general model-independent method has been developed to analyze multi-measurement NMR data that is governed by distributions of more than one property; e.g., T2, T1, and diffusion (Cao Minh et al., 2003). The objective of the method is to present 4 In the first case study, a sand was found where a routine formation pressure gradient was drawn from formation pressure data. The initial interpretation of this interval showed it to be strictly oil bearing (Fig. 5). Lowresistivity response in this interval suggested that the sand might indeed contain water or be water bearing. Other sands above and below the interval were interpreted as being oil bearing, and all the formation pressure points were observed to lay on a single oil gradient line. Therefore, classical pressure gradient interpretation techniques dictated that the sand was most likely oil bearing. However, NMR fluid typing data from this same interval strongly contradicted this basic assumption. The D-T2 map clearly shows the zone to be water bearing (Fig. 5). Based on NMR fluid and resistivity, the interpretation of the fluid content of this interval was changed and the zone has subsequently been interpreted as water bearing. Following the NMR data acquisition, fluid sampling in the zone has proved that the zone is indeed water bearing. In the second case study, neutron-density separation and crossover had indicated the fluid type with a low degree of confidence in the interval of interest. Formation pressure gradient analysis suggested that the sand contained dry gas (Fig. 6). A number of NMR fluid station measurements were conducted within this interval (Fig. 7). Examining the D-T2 maps for all of 1 With next generation NMR logging tool that is currently available, NMR fluid typing can be carried out in continuous mode.

5 the stations (from bottom to top) revealed the following results: 1. The two lowermost stations (at 4,032 and 4,036 m) indicate water is present (Fig. 8). 2. The station at 4,027 m most likely suggests high-gor oil, as do the two stations at 4,013 and 4,010 m (Figs. 8 and 9). From past experience, it is quite common to observe the coherence peaks on the D-T2 map shift to the top left when high-gor fluids are present. Similar observations have been made in many other parts of the world, and it is customary to interpret these points as oil with high GOR or gas condensate. In the pressure-temperature domain of phase change, variation between volatile oil and gas condensate could be subtle and the NMR fluid technique might not resolve it sufficiently. However, an important result is that the NMR fluid technique has eliminated the possibility of these points being dry gas points. The uppermost point at 3,999 m suggests gas characterized by high diffusion (Fig. 9). It is interesting to note that if one looks closely at the neutron-density crossover separation at this point, there is slightly more separation compared to stations below. In these examples, the NMR fluid stations corroborate inferences of fluid type made strictly from the character of neutron-density separation within this interval. Fluid sampling from this same interval has subsequently shown it to contain gas condensate. The two case study examples presented illustrate the complexity of identifying fluid types in deepwater Nigeria as well as the benefits that NMR fluid typing technique brings to deepwater formation evaluation. Undoubtedly, formation pressure gradient analysis technique are inherently accurate, robust and historically tested. However, in these complex fluid situations where there are subtle variations in water, oil, gas and gas condensate, pressure gradient analysis is sometimes insufficient to confidently predict fluid types. Typically only a few formation pressure points (three to four) are present in any given interval and used to establish a formation pressure gradient. A slight shift or uncertainty in either in pressure and / or depth using these points, therefore, can lead to a misinterpretation of fluid type. BENEFITS, IMPLICATIONS, AND LESSONS LEARNED By combining NMR and the NMR fluid typing technique with other conventional log data and formation pressure gradient analysis and fluid sampling, two objectives are met: a) optimization of the formation evaluation program in place with respect to data gathering and cost effectiveness, b) improved reservoir description, with direct impact on the completion program and field development planning. The field development costs in deepwater Nigeria are extremely high. At the same time, huge financial investment has to be made based on information from small numbers of wells. In the early stages of the Erha development, facilities, such as floating production facilities and sub-sea equipment, were engineered based upon fundamental assumptions of reservoir fluid content and rock quality taken from a limited amount of data acquired in the three available exploration and appraisal wells. As the development has proceeded from the appraisal stage and into the development drilling phase, it has become increasingly important to properly characterize the reservoir and fluid content in the most cost-effective manner possible. This has ensured that expenditures on well completions, additional facility planning, and field development continue to be well justified and effective in design. Our experience with a number of wells in the Erha field has demonstrated that reservoir fluid content is often complex with very subtle changes not readily or accurately identified using classic interpretation techniques. Moreover, water has also been found unexpectedly within the field in isolated sands in inverted traps. Because of the presence of clay and invasion by oil-based drilling fluids, neutron-density separation is not always a reliable method to distinguish different fluid types. Formation pressure gradient analysis is a dependable tool for fluid identification, but it is associated with long rig time and cost, and also as illustrated above, quite often this approach is inadequate in identifying fluid types in deepwater Nigeria fields. Fluid sampling and downhole optical fluid analysis are more definitive techniques but are also associated with high cost or heavy sample contamination by drilling fluids. NMR fluid typing is a very useful method in the deep waters of offshore Nigeria because it provides an independent and additional formation fluid type measurement that can significantly improve fluid characterizations. Integrating this technique with other openhole logging data is a highly desirable formation evaluation method. As a best practice for formation evaluation in the Erha field, it has become commonplace to initially examine the openhole logs, especially the neutron-density separations. It is then followed by a number of NMR fluid station measurements, then formation pressure FFF 5

6 gradient analysis, and finally fluid sampling and downhole fluid analysis in more conjectural points to reduce the maximum amount of uncertainty in identify fluid types. The NMR fluid technique, however, does have limitations in deepwater Nigeria reservoirs. Because mostly light oils are encountered, they tend to overlay water on D-T2 maps (at high T2 and on the water line). With increasing GOR, coherence peaks of oil tend to shift towards top-left and are commonly observed to lie on the theoretical water line. Without other independent information such as resistivity, it becomes increasingly difficult to distinguish this NMR signal from water. Another limiting factor to the effectiveness of the NMR fluid typing technique is mud filtrate or whole mud invasion. As the NMR fluid station measurement is taken very close to the wellbore with a very shallow depth of investigation, original formation fluid characters can be masked with oil based mud filtrate. Moreover, this invasion can alter the original wettability of the formation and could complicate NMR fluid signals. Another complication that is commonly observed in deepwater Nigeria formations is solid mud invasion (often times termed as whole mud invasion ). This negatively impacts NMR fluid methods in that this type of invasion limits a reliable interpretation of D-T2 maps. For these reasons, only a limited number of sparsely populated NMR fluid stations can be insufficient for definitive fluid characterization. Therefore, it is important to ensure that the formations in question are covered by an adequate number of NMR fluid stations to make sure enough usable fluid stations are available to make a conclusive interpretation of fluid type. CONCLUSIONS REFERENCES uncertainty in complex formation and fluid situations. Fluid sampling and optical fluid analysis downhole significantly improves fluid characterization, but can also be costly and occasionally sometimes suffer from drilling fluid contamination problems. The NMR fluid technique brings a new insight into fluid typing. By simultaneously measuring NMR relaxation and diffusion, fluids can be distinguished as diffusion coefficients of water, oil, and gas are widely separated. However, the NMR fluid method can also be impacted and limited in effectiveness by oil-based drilling fluid invasion as with the fluid sampling and optical fluid analysis techniques. As a best practice, an improved scheme for formation fluid evaluation is found with the integration of all these methods, i.e., openhole logs, NMR fluid method, formation pressure, and fluid sampling that optimize the data acquisition program and significantly reduce fluid typing uncertainty. The new-generation wireline NMR tool currently available is a major benefit in that it is a continuous (non-stationary) measurement and, most importantly, multiple depths of investigations will help to identify native fluid beyond the invaded zone. Allen, D., Crary, S., Freedman, B., Andreani, M., Klopf, W., Badry, R., Flaum, C., Kenyon, B., Kleinberg, R., Gossenberg, P., Horkowitz, J., Logan, D., Singer, J., and White, J., 1997; How to use borehole nuclear magnetic resonance: Schlumberger Oilfield Review, vol. 9, no. 2, p In an expensive deepwater exploration and appraisal scenario such as the Erha field in offshore deepwater Nigeria, accurate fluid characterization is essential for successful field development. Subtle variations of water, oil, gas, and condensate make fluid characterization difficult. Conventional openhole logs, especially neutron-density separation, are not always sufficient for dependable and accurate fluid typing. Formation pressure gradient analysis is a dependable tool for evaluating fluid content, but it can be costly and may have some Bouma, A. H., Sedimentology of Some Flysch Deposits- A Graphic Approach to Facies Interpretation. New York: Elsevier. Cao Minh, C., Heaton, N., Ramamoorthy, R., Decoster, E., White, J., Junk, E., Eyvazzadeh, R., Al-Yousef, O., Fiorini, R., and McClendon, D., 2003, Planning and interpreting NMR fluid characterization logs, SPE presented at the SPE Annual Technical Conference and Exhibition. Coates, G., Xiao, L., and Prammer, M., 1999, NMR logging: principles and applications: Gulf Publishing Company, Houston, Texas. 6

7 Freedman, R., Lo, S., Flaum, M., Hirasaki, G.J., Matteson, and Sezginer, A., 2001, A new NMR method of fluid characterization in reservoir rocks: Experimental confirmation and simulation results: SPE Journal, vol. 6, no. 4, p Tech University. Prior to his Nigeria assignment, Souvick worked in Thailand, Indonesia, Saudi Arabia, and Bahrain. He is member of SPWLA and SPE. Freedman, R. and N. Heaton, 2004; Fluid Characterization using Nuclear Magnetic Resonance Logging, PETROPHYSICS, vol. 45, no. 3. FFF Kleinberg, R., and Vinegar, H., 1996, NMR properties of reservoir fluids: The Log Analyst, vol. 37, no. 6, p Slijkerman,W., Looyestijn, W., Hofstra, P., and Hofman, J., 1999, Processing of multi-acquisition NMR data, SPE presented at the SPE Annual Technical Conference and Exhibition. ACKNOWLEDGEMENTS The authors wish to express their appreciation and special thanks to Art Schnacke and Mark Bowers for their critical reviews of this paper. They would like to thank Bruce Kaiser and Jennifer Smith to review the manuscript. They would also like to thank the Nigerian National Petroleum Company, Esso Exploration and Production Nigeria Limited, Schlumberger, and Shell Nigeria Exploration and Production Company Limited for their approval to publish this paper. ABOUT THE AUTHORS Russell W. Spears is a petrophysicist for ExxonMobil Development Company working with deepwater Nigeria projects in Houston. Russell holds a BS in geology from the University of Georgia, attended Oxford University, Oxford, England, and holds an MS in geology from Louisiana State University. He has petrophysical experience in several unique geological environments, including offshore deepwater Nigeria, offshore California, Mobile Bay, onshore Louisiana, the Gulf of Mexico, onshore Alabama, and onshore Florida. Russell currently serves on the SPWLA Long-Range Steering Committee, is an SPWLA Distinguished Speaker, is currently nominated as a regional director of the SPWLA, and has previously served as Secretary for the New Orleans SPWLA local chapter. Russell is also member of the SPWLA and the AAPG. Souvick Saha is a petrophysicist working for Schlumberger and currently based in Lagos, Nigeria. Souvick holds an M.Sc in applied geology from IIT (Indian Institute of Technology) and a PhD from Texas 7

8 Fig. 1: Location map of the Erha field, OPL 209, deepwater Nigeria. Fig. 2: Typical succession of lithofacies within a classic Bouma sequence turbidite reservoir (modified from Bouma, 1962). 8

9 TE FFF B 0 Polarization B 1 NMR Decay Signal Inversion Amplitude (k) T 2 (k) Fig. 3: Illustration of NMR measurement principle polarization of hydrogen protons, NMR decay signal followed by inversion to generate T2 distribution. log(d(cm2/s)) Gas Water Bound water D-T2 map oil Oil log(t2(s)) gas obm Fig. 4: D-T2 map - combining Diffusion (D) and Transverse Relaxation (T2). 9

10 A Fig. 5: From left to right, tracks show gamma ray, formation pressures & gradient, drawdown mobility, neutrondensity and resistivity logs. Pressure gradient in the sand (A) suggests oil-bearing formation. Green arrow indicates the depth where NMR fluid station measurement was taken. D-T2 map indicates free fluid to be water with oil based mud filtrate. 10

11 FFF Fig. 6: From left to right, tracks show gamma ray, formation pressures & gradient, drawdown mobility, neutrondensity and resistivity logs. Pressure gradient analysis suggests dry gas. 11

12 3999m 4010m 4013m 4027m 4032m 4036m Fig. 7: Conventional triple-combo LWD logs (from left to right gamma ray, resistivity and neutron density). Green arrows indicate NMR fluid station depths. Neutron-density was missing towards the bottom. 12

13 FFF 4027m: High GOR oil 4032m: Water 4036m: Water Fig. 8: Conventional triple-combo LWD logs (from left to right gamma ray, resistivity and neutron density). Green arrows indicate NMR fluid station depths; corresponding D-T2 maps are shown. 13

14 3999m: Free gas 4010m: High GOR oil 4013m: High GOR oil Fig. 9: Conventional triple-combo LWD logs (from left to right gamma ray, resistivity and neutron density). Green arrows indicate NMR fluid station depths; corresponding D-T2 maps are shown. 14