JFES SYMPOSIUM CORE TO LOG INTEGRATION LEADS TO IMPROVED NMR LOG INTERPRETATION IN EXTRA HEAVY OIL RESERVOIRS, ORINOCO HEAVY OIL BELT, VENEZUELA.

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1 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 JFES SYMPOSIUM CORE TO LOG INTEGRATION LEADS TO IMPROVED NMR LOG INTERPRETATION IN EXTRA HEAVY OIL RESERVOIRS, ORINOCO HEAVY OIL BELT, VENEZUELA. Miguel Expósito 3, Jose Marcos 2, Jhonny Casas 3, Olga Garcia 1, Carlos Minetto 2,, Jesus Ernandez 4 (1) PetroCedeno former SINCOR, (2) Baker, (3) Gazprom LA, (4), Pdvsa This paper was selected for presentation by the JFES program committee following the review of abstract submitted by author(s). ABSTRACT NMR logging in extra heavy oil reservoirs is known to be very challenging for several reasons. The very fast relaxing extra-heavy oil components cause porosity under-estimation compared to conventional log and core porosities even when logged with sub-ms inter-echo time, TE. Consequently, permeability estimation is adversely affected. Both conventional petrophysics and non-conventional NMR processing method were used to identify extraheavy oils and quantify the heavy oil saturations because the traditional NMR hydrocarbon typing techniques, which are based on polarization and/or diffusion contrasts between water and oil phases, are not robust enough when in presence of extra heavy oil (API between 7.2 to 8, and viscosities ranging from 2 up to 6 cps dead oil). The methodology is supported on NMR laboratory studies performed on cores. Oil saturated cores were used to identify the different NMR responses. In Orinoco Heavy Oil Belt, Oficina Formation (the main reservoir) is characterized by coarse grain sands in a fluvial-deltaic environment. Laboratory measurements were focused on quantifying NMR T2 distributions of heavy oil and water, apparent and absolute hydrogen index (HI) and the viscosity of the heavy oils. The NMR core measurements, 52 NMR logs and 9 cored wells, enabled the construction of a methodology for processing, that improves the determination of petrophysical properties, e.g., porosity, permeability, BVI, BVM, estimates from NMR logs acquired in this extra heavy oil field. The approach starts using the Gamma function as an inversion algorithm and is based on recognizing fragments of the T2 distributions associated with each of the fluid volumes present in the pore space. An algorithm was developed to calculate the individual fluid contributions. Subsequently, we apply a volumetric based apparent porosity correction by taking into consideration the apparent HI of the extra-heavy oil. The corrected results for porosity and irreducible water agree very well with conventional core analysis. In addition, permeability values estimated from these NMR logs were initially calibrated to core permeability where core data are available and two different empirical permeability equations are used for water and oil zones, respectively. The calibrated permeability model is then applied to NMR data acquired from many new wells. Later, core analysis on a second sets of wells indicate that the permeability models work satisfactorily for those new wells, proving that the calibrated permeability models and the porosity correction method are applicable and valid in Faja del Orinoco extra-heavy oil fields. INTRODUCTION In the study area, the Oficina Formation (Miocene) progressively onlaps southwards against older rocks ranging from Cretaceous to Cambrian. The stratigraphic framework established is based on the recognition of key stratigraphic surfaces correlatable over the entire area (Casas, Gonzalez and Marfisi, 27) and mapped on 3-D seismic data. Lower Oficina Formation (Morichal Member) can be divided into a lower and an upper part. Both parts are divided into three stratigraphic units (F D and C A, from the base upwards), In the southwestern area, stratigraphic units F, E, and D are interpreted as being deposited in a fluvial-dominated environment, with relatively straight rivers typified by erosive bases and a braided talweg pattern around offsetting repetitive bar forms. These units show a high net to gross ratio. Unit C is interpreted as being deposited in a proximal deltaic environment typified by distributary channels and mouth bars with probable tidal influence (Labourdette, Casas and Imbert, 28). The facies diversity of Unit C is relatively wide, and the net to gross ratio is relatively low. At the top, Unit C is composed mainly of shales, but in some areas, thick sands have been deposited. These sands have probably been deposited as the filling of incised valleys. The uppermost reservoirs called units B and A were deposited on a lower delta plain that is characterized by 1

2 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 relatively wide meandering channel belts with tidal influence. Sand was deposited mainly as large, composite point bars. The lower fluvial section (D/E/F stratigraphic units) contains the aquifer in the area and is mainly composed of sandy channel/bars and crevasse splays units in a fluvial braided setting. In each of these stratigraphic levels, the channel/bar facies association forms elongated channel belt complexes or fairways, crossing the studied area with a general NNE-SSW trend. This sedimentological setting allows lateral and/or vertical communication in particular areas that could explain complex fluid distribution/communication (Marcos et al, 27) The Lower Oficina Formation (Morichal Member) is the main reservoir, and is divided into Deltaic and Fluvial sands. These sands are non-consolidated and show high porosity and permeability values. Their main differences between both, are the Net to Gross, since Fluvial sands have a lot better Net to Gross across the field. The Orinoco Heavy Oil Belt development considered initially the acquisition of NMR logs in order to help characterize the reservoir properties, however the initial phase of data collection had a big challenge in obtaining quantitative interpretation of the NMR logs, especially when related to density-neutron combination due to the heavy oil effect that caused a fast relaxation, thus no real porosity and permeability could be obtained from the original processing methods, and only water encroachments detection was the primary use of this technology. According to the basic NMR interpretation it is suggested that 33 ms should be a standard cut off to define non movable from movable fluids specially for lighter oil (see figure 1a), notice that everything below this value could be consider either Clay Bound or Irreducible Water Rock Matri xx Minimum value ca Measure by Dry Cla y CBW: Clay Bound Water CBW BVI Cla Boun Wate i Capil r Boun Mobil e FFI I Hydrocarb on CB B (Oil+Water+Invas FF.1ms.5 ms 4 ms I 33ms End result Heavy oil sign CB B I ~1 ms BVI: Bulk Volume Irreducible 1.a. From Light to Medium Condition FFI (Invasion and Wate FFI: Free Fluid Index 1.b. Heavy Oil Condition Figure 1 (1a T2 distribution for lighter oils and 1b. for heavy oils) Junin s case is totally different as presented in figure 1b where the oil signal is much faster than CBW or BVI. In order to properly attacked the problem a jointly study was designed with NUMAR to study the heavy oil behavior in poorly consolidated sands, aiming to obtained a set of corrections and equations that possibly help in the better estimation of the petrophysical properties in the reservoir (porosity and permeability mainly) After this work was competed all results were evaluated in new wells were NMR (mainly MRIL type C and some PRIME) logs were acquired with some success although a bit more work was need it in order to properly match the total volumes in the reservoir, due to local changes in rock and fluid properties across the area. To continue the work a methodology was design for this specific case that allowed to estimate porosity and permeability from NMR logs, at this stage the computation were matched with the available core data in the cores across the field with excellent results in terms of porosity and specially permeability, over which big efforts have been done in order to approach reliable values in the high permeability reservoirs FIRST STEPS The unconsolidated character of the sands in the Lower Oficina Formation in the area, plus the heavy oil located in these sands was a subject of a study that was carried out by NUMAR between 21 and 22 where 1 core samples, a crude oil was measured using NMR and calibrated to standard core analysis. The idea was to apply these results in future NMR log interpretation to obtain quantitative values of the petrophysical properties as well as fluid (viscosity). The initial outline of the work also aimed to confirmed current logging parameters (WT and TE). NUMAR study main goals were the following 1. Characterization crude oil at reservoir temperature (125ºF) 2. Evaluation of relaxation distributions of fresh-state samples 3. Verification of formation porosity and log response 4. Determination of a formation specific permeability relationship 5. Determination of formation specific parameters to determine BVI (irreducible) from the downhole tool 6. Determination of movable fluids from log responses 7. Characterization of wettability of the rock samples The outcome was a group of customized equations that allow a first phase of quantitative evaluation of the NMR data.

3 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 LABORATORY RESULTS The characterization of the crude oil and other relevant results from this study are presented below Crude Oil Properties Temperature (Deg. F) Primary Mode No Gradient T 2 ms TE Primary Mode No Gradient T 2 ms TE Primary Mode No Gradient T ms TE Primary Mode T 1 ms TE Hydrogen ms TE Viscosity, cp Where T2 Temperature Relationship is: T 2 = E-4 * (Temperature) and T 1 = E-1 * (Temperature) T1 and T2 in milliseconds and Temperature in F Viscosity - Temperature Relationship is: Viscosity = E15 * (Temperature) Temperature in F and viscosity in cps Hydrogen Index (Volume Ratio) - Temperature Relationship HI = E-3 * (Temperature) E-1 BVI Determination: The average of the individual sample cutoffs can be used to define the BVI component for each data set. The average T 2 cutoff values as well as the variability of the cutoffs for each saturation condition are as follows: For zones flushed by the mud filtrate the permeability was assessed Model Name Coates II Coates IV 1% Brine Saturated Distributions Equation K=MPHI 1(1/.6761)(log(FFI/(BVI.133)))) K=((MPHI/.139)2 (FFI/BVI)).6579 Wettability, tests were performed on 1 core samples available, the results lead to believe the these rocks are to be between mixed to oil-wet wettability. It is difficult to see the effects of this type of rock wettability via NMR, because the bulk oil relaxation time is so fast, that undercall effects mask the shift due to surface effects when the crude is introduced into the plug samples. METHODOLOGY After the study with NUMAR was concluded, 1 additional NMR logs were acquired and processed according to the NUMAR results, however it was noticed that especially in oil legs the saturation was overestimated (Figure 2) Overestimation of the oil volume Saturation State Average T 2 Cutoff Range of T 2 Cutoffs 1% Brine 1 ms 23 to 145 ms Oil/Brine 1 ms.4 to 48 ms These variations in T2 cutoff range may cause inconsistencies in MRIL interpretations. For Oil and brine systems permeability was assessed by different models as follow: Model Name Oil/Brine Saturated Distributions Equation Low permeability estimation Porosities do not show good match is shaly sands Figure 2: shows overestimation of oil volume Incorrect BVI estimation After this first attempt to upscale the results from the NUMAR study it was decided to launch a small project that handle the specifics of each area across the field and in the different sands, in such way that more control in computations could be on hand. Coates I K=((MPHI/4.726) 2 (FFI/BVI)) 2 Coates IV K=((MPHI/.9571) 2 FFI/BVI)).4823

4 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 and combined effects of mud filtrate in high permeable rocks. Hydrogen Index came to a further study (Deleesnyder, 24) where NMR techniques were viscosity, HI and T2 are all related and the T2 is directly linked to HI, and the type of crude in the oil column Figure 3: Example of the CBW volume determination based on statistical similarity between T2 Components and GR The unconsolidated character of the sands in the Oficina Formation plus the heavy oil located in these sands was a subject of a study carried out by NUMAR between 21 and 22, a crude oil was measured using NMR and calibrated to standard core analysis. The idea was to apply these results in future NMR log interpretation to obtain quantitative values of the petrophysical properties as well as viscosity. The initial outline of the work also aimed to confirmed current logging parameters (WT and TE). The outcome was a group of customized equations that allow a first phase of quantitative evaluation of the NMR data. A basic consideration of the T2 responses for each volume was taken into account to appropriate describe the quantities in the pore space, the initial scheme adopted to identify the volumes was based on time (T2 in ms): Further refinement of our computation was performed based on the modeling of viscosity and HI with good results, as seen in Figure 4 where there s a good match in porosity, permeability is reasonable and oil volume is better. Better permeability estimation Better match between porosities (HI driven) Oil volume Estimation using NMR Better BVI Estimatio n Figure 4: shows a better estimation of petrophysical parameters After these tests on processing was performed a full field re-processing stage was performed on 52 wells with field data (second generation tools) Parameter BVO CBW BVI BVM Where: T2 Window.5 to 3.6 ms 3.6 to 11.6ms 11.6 to 45 ms 45 to 722 ms New NMR results were taken on a well by well basis and calibrated to core data, key wells first where more information is available. PetroCedeno (one of the state owned companies producing oil from Junin area in the Orinoco Heavy Oil Belt), developed a basic rule of calibration which varies per reservoir, also based on these new logs and core data a full review of all permeability calculation was performed across the different reservoirs (deltaic and fluvial) BVO CBW BVI BVM Bulk Volume Extra Heavy Oil Clay Bound Water Bulk Volume Irreducible Bulk Volume Movable In Figures 5 and 6A an example of calibration performed, using re-processed NMR data, an overall agreement on petrophysical properties can be observed in the logs and in the field when using this information to characterize the reservoirs Corrections to this calculation are only by HI. It is important to highlight that above 722 ms there s a high volume of mud filtrate not totally polarized, this phenomena probably happens due to wettablity changes All calibrations were performed using core data available at the time of the study starting in 23 through late 24, after that new NMR data along with core analysis became available, so the results shown here are based in a much larger number of samples. Some of theses results

5 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 were revisited in order to obtain a much better match, in the old and new wells..2 OHMM 2 CALI_1 RSHALLOW_MATCH_1 DEPTH TVDSS 6 IN 16 FEET FEET.2 OHMM 2 GR_NORM_1 RXO_MATCH_1 GAPI 2 C_PERMA_1 1 MD 1 RDEEP_MATCH_1.2 OHMM 2 C_POR_1 6 % NPHI_C_M_1.6 V/V RHOB_ G/C C_POR_1 6 % POR_1.6 V/V C_POR_1 6 % MPHS_1 6 % COAL_1 logical 1 BVWXO_1 1 V/VF BVW_1 1 V/VF PHIE_1 1 V/V VOL_WETCLAY_1 V/V 1 C2M C2L 2 D1 D2 25 D3 E Figure 6A: shows in track 1 a good correlation between calibrated MRIL and core permeability. 215 taceous Figure 5: shows in track 1 a good correlation between MRIL and core porosity Core porosity calibration was performed first, and from this permeabilities were obtain from the Coates equation adjusting the constants m, n, c to the values obtain when calibrating to core data, 1.5,.66 and.2 where obtain for these constants. A transform to apply the results of the permeability was design in order to extend and to increase the frequency of this data to rest of the wells in the area without NMR data. The main goal was to have a reliable porosity permeability transform related to core and NMR, that allow us to relate it to other wells without core or NMR, from this computation the following equation was obtain K abs 2 ( * φ * φ = 1 ) In Figure 6B an example of this computation in presented as, the weak point of this law is located at very low permeabilities (<8 md) were due to the lack of data the law does not go as low as that, however is important to mention that at these low permeabilities the rock is not considered reservoir is mainly composed of several interbedded sands with poor rock properties, which by the way are linked to the cut offs in the area to define pay. Also very high (> 7 su) were measured in this hetherolitic sands. Figure 6B: shows an example of a later application of the permeability transform to a new well, in track 12 a good agreement for thick sands and reservoir lithofacies, major problem still the low permeability hetherolitic streaks due probably to the lack of data and vertical resolution of logs (bed < than 5 inches). Also notice that oil has a very fast relaxation time across this succession. The main interest of all this project was to obtain rock properties calibrated to rock and fluids, this project is still active since new core data was acquired and analyzed, however the outcome of the study was presented early in 25 where some of the reservoirs were mapped in terms of the genetic facies, and populated in 2D as well as 3D using rock properties derived in the study. Several stratigraphic successions were described using this methodology for the purpose of this paper and some examples are shown in figures 7, 8, 9, 1 and 11. Figure 7 shows the different lithofacies described in the study area base upon grain size and sedimentary structures. With this lithofacies codification, a vertical facies association was established per each genetic facies interpreted (Figure 8). Once extrapolated the sequence stratigraphy correlation and the genetic correlation between bodies and wells, a net sand map showing

6 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 geometry and orientation of each genetic body was interpreted (Figure 9). FB FA FC OA OB OC PB PA PC GE NC QD GD GC NB ND QC QE GB HD HB IE IB ID IC JB JD GA NA QA QB MD ME RD HC MC RC WB XA WC RA WA SE SC IF LE YC VD LD VC LC SB YB IA SA SD VB YA LA LB UC UD TB TC ZC KA JA ZB UB KC UE ZA JC UA TA 1 NET SAND THICKNESS VSh less than.4 Coal less than 1 Figure 9. Net sand mapping showing geometry and orientation of the two main facies association interpreted (Pointbars and crevasses splays). With this methodology, log properties such as Vsh, saturation, porosity and permeability can be defined for each genetic facies association (Figure 1 and 11), in order to properly populate 3D models. Figure 7: shows the different lithofacies in the area of study, in the upper side of the figure the reservoir and below non reservoir lithofacies Phie % Vol_Wtc% Swe% Point Bar Crevasse Figure 1. Log Properties distribution (Phie, Vsh and Swe) per genetic facies association (values in %). Figure 8. Lithofacies vertical architecture within a genetic facies association interpreted as pointbars Point Bar Crevasse Splay Figure 11. Log Permeability distribution (md) by genetic facies association.

7 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 Towards the dynamic model for each reservoir we started to calibrate the NMR to SCAL measurements, the first results of this was the calibration of the BVI volumes, the lower reservoirs are still under evaluation but some relationship between permeability and Swirr were derived based on grain size and lithofacies, this aiming to initialize the model where no OWC is present, height functions were used when OWC is present. Figure 12 shows these results. Swirr max = 32 % Saturación de agua irreducible (%) Permeabilidad (md) Figure 13: In track 4 is possible to see how different is the relaxation in the Eastern side of Faja, where oils are not so viscous and viscosities will range from 5 to 5 cps FUTURE WORK Extend and apply all transforms and equations derived to the new wells, mainly all acquired with brand new NMR technology and see the differences. Integrate all new core data currently undergoing different lab tests, some at CCA some others at SCAL Improve lithofacies prediction by adding all new core description, see if changes are required to the sedimentological models previously defined based in old and existing cores. Figure 12: Swirr and Permeability relationship, depending on grain size and Lithofacies (Z axis) It is also good to mention that the methodology followed here to process NMR data is particular and probably is for use in the Western side of the Faja, was the oil behavior is unique. Where the reservoirs are composed with extra heavy oil and its relaxation time is faster than shales (Figure 6B) and the lack of compaction, the shallow depth of these reservoirs (high viscosity, low pressure, less gas in solution) results in an unique feature, more toward the East of Faja these features disappear and the oil becomes less viscous. More pressure and dissolve gas will complicate the analysis, T2 in oil will mixed with clay fraction making the analysis more complex and no to easy. In this case we are building a case with different oils and intensively acquiring NMR using the standard methodology in order to achieve the same level of success (Figure 13). Consider the new method of inversion to obtain T2 distributions using Gamma functions with the old technique. (Part of this has been already proposed and the work is currently underway for the Eastern side of the study area) CONCLUSIONS AND RECOMMENDATIONS This methodology proposed has given results when processing old NMR data (MRIL type C and PRIME), the use of core material allowed us to achieve an acceptable permeability as well as BVI very useful in reservoir models All the results were extrapolated to wells without NMR data for a later use in mapping reservoir properties for all stratigraphic levels. This methodology is basically dependant of core data and fluid availability, being the later the most difficult to manage when measuring in situ conditions, since is too viscous and it varies vertically and laterally. Also all experiences had trouble restoring the crude conditions, since no gas is possible to put in the system. The same routine should be performed in fresh samples with bigger dimensions (a foot or a meter)

8 The 14th Formation Evaluation Symposium of Japan, September 29-3, 28 When dealing with lab measurement it is important to keep in mind the scaling problem higher S/N relations than in logging, also the size of each sample could introduce some problems when calibrating In general the results obtained so far are logical although not perfect, this process has to be iterative and dependant at all stages of the material available. Also it is subject to be modified at any stage due to the continuing change in tools and method of processing. REFERENCES Casas, J., Gonzalez M., and Marfisi, N. (27) Genetic Facies interpretation in vertical/slanted/horizontal wells and its integration within the geological model (Oficina Formation, Sincor Field, Orinoco Heavy Oil Belt, Venezuela). IX Venezuelan Geological Congress, Caracas, Venezuela, October Deleesnyder, M, 24 In-Situ Heavy-Oils Viscosity Determination using NMR and Conventional Logs: Application to a Real Example, SPE International Thermal Operations and Heavy Oil Symposium and Western Regional, paper Labourdette, R. Casas, J. and Imbert, P. (28) 3D Sedimentary modelling of a Miocene deltaic reservoir unit, SINCOR Field, Venezuela: A new approach. Journal of Petroleum Geology, Vol. 31(2), pp 1-18 Marcos, J., Pardo, E., Casas, J., Delgado, D., Rondon M. and Exposito, M. (27) Static and dynamic models of formation water in SINCOR area, Orinoco Belt, Venezuela. Memoir SPE LACPEC, Buenos Aires, Argentina (April 15-18) NMR Logging Principles and Applications. Halliburton Energy Services Publication, 1999 NUMAR, 22 NMR Core and Fluid sample Measurement Study phase I and II. Internal report. ACKNOWLEDGEMENTS The authors wish to express their appreciation to PDVSA who allowed us to publish the results and to Baker and NUMAR for being part of this study.