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SPE 141783
Utilizing NMR and Formation Pressure Testing While Drilling to Place Water Injectors Optimally in a Field in Saudi Arabia Dhafer Al-Shehri, and Mohammed Kanfar, SPE, Saudi Aramco; Yusuf Al-Ansari, and Syed Abu Faizal, SPE, Baker Hughes
Copyright 2011, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Middle East Oil and Gas Show and Conference held in Manama, Bahrain, 25–28 September 2011. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.
Abstract The presence of tar or heavy oil that does not flow using conventional production technologies brings numerous challenges during field developments. Tar, acting as a permeability barrier, would often break flow or pressure communication from the aquifer to the oil zone. This results in inadequate pressure support, which is necessary for sustaining production levels and maximizing oil recovery. One of the key issues in developing a field with known tar mat accumulation is to optimally place injectors away from the tar. The problem becomes more complicated when the exact location of a tar mat is uncertain either laterally or vertically. Tar mats usually are neither flat nor uniform in thickness across a field. These uncertainties pose a challenge in planning wells especially water injectors. Detection of tar is critical for reservoir characterization, reserves calculation and well placement. Direct and indirect techniques are employed to detect tar including core analysis, well testing, wireline logging and Pyrolitic Oil Productivity Index (POPI). These measurements are good indicators of tar; however, the challenge is to identify the tar while drilling the well. Early detection requires the deployment of logging while drilling (LWD) technologies for real-time interpretation of data. In order to accurately identify tar in reservoir sections in real-time, integrating conventional LWD measurements with new technologies such as the slim hole Nuclear Magnetic Resonance (NMR) and the formation pressure measurements while drilling (FPWD) is necessary. This will allow for timely adjustment to the well path and prevent costly remedial actions This paper discusses successful real-time application of slim-hole NMR and FPWD technologies to detect tar and optimally place water injectors. This is demonstrated with two case studies involving extended reach power water injectors. Introduction Many reservoirs in the Middle East are characterized by a layer of heavy immobile oil, also referred to as tar mats, creating additional challenges regarding pressure support and recovery strategies. Tar mats are present in Middle East reservoirs, including Iraq, Kuwait Qatar, Oman, Abu Dhabi and Saudi Arabia.1 Tar mat in these reservoirs is found as highly viscous immobile accumulations between an underlying aquifer and a lighter oil phase above. One of the main issues of such reservoirs is that tar acts like a barrier between the oil zone and the aquifer impeding the natural bottom water drive and rendering water injection into the aquifer for pressure maintenance ineffective. The complexity of reservoir management in these types of reservoirs is increased with the uncertainty of lateral and vertical extent of tar mats throughout the field. One of the most effective strategies in developing these fields is placing the horizontal injectors as deep as possible just above tar. The uncertainties related to the tar make it extremely important to detect it early. Required adjustments to well plans can be made
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accordingly. Integrated workflows including conventional logs, NMR, FPWD and other tar indicators have been effectively employed to drill long horizontal wells in carbonate reservoirs characterized with tar accumulations. Tar Identifying Technologies Nuclear Magnetic Resonance While Drilling.
Figures 1 and 2 are schematics of the NMR LWD tool and the sensor sub arrangement respectively. The sensor sub consists of two arrays of permanent magnets that generate a static magnetic field while the coil antenna generates the radio-frequency. The permanent magnets in the tool polarize the formation near to the wellbore forcing the hydrogen nuclei in the pore fluid to align according to the direction of the magnetic field. The formation is then subjected to a sequence of radio-frequency pulses perpendicular to the magnetic field. This causes hydrogen nuclei to reorient frequently and produce a characteristic decaying signal. Evaluation of the amplitude and decay rate of the signal yields information about the porosity, fluid content and rock.
Figure 1. 4 3/4" NMR LWD tool assembly for 5 7/8”, 6 1/8” hole size applications.
Figure 2. NMR LWD sensor arrangements.
Nuclear Magnetic Resonance (NMR) directly measures fluid-filled porosity and allows differentiation between movable and bound fluids. The main advantage of NMR porosity over porosity from other logging tools is that the NMR porosity is independent of the type of lithology. The NMR measurement does not need radioactive sources, which is the most obvious safety aspect over nuclear methods. From a petrophysical point of view the NMR measurement delivers much more information about the formation than porosity only. This includes:
• Partial porosities: Clay Bound Water (CBW), Bulk Volume Irreducible ( BVI), Bulk Volume Movable (BVM) • T2 relaxation time distribution / pore size distribution • Permeability index • Hydrocarbon typing • Hydrocarbon saturation
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NMR plays an important role in identifying tar or low permeable zones. In tar, the NMR total porosity can show a deficit compared to total porosity from conventional logs such as density and neutron (Figure 3). This is due to the fact that the decay times of the portion of NMR signal measuring solid hydrocarbon phase are too fast to be detected by the logging tool. Another good tar indicator, known as excess bound fluid, is the difference in bound fluid porosity from NMR log and the bulk volume of water from conventional logs. In case of tar the excess bound fluid volume is a positive value. Detailed explanations of this concept can be found in the paper by Akkurt, et al.2 Furthermore, reservoir fluid viscosity can also be determined using NMR measurements based on the fact that higher viscosity fluids show up at shorter T2 times.3,4
No tar indicated: NMR porosity reads equal to
total porosity from neutron-density: no excess bound fluid
Tar indicator: T2 is shortened
Tar indicator: NMR porosity deficit (NMR reads less than
total porosity)
Tar indicator:Excess bound fluid reads high
Figure 3. Tar indication and characterization from NMR by porosity deficit, excess bound fluid, and T2 distribution shift. Formation Pressure While Drilling.
Formation pressure while drilling (FPWD) was introduced to measure accurate formation pore pressure in real-time. FPWD has found many applications over the years including estimating near wellbore mobility, reservoir connectivity and equivalent circulating density (ECD) management.
FPWD operates by a brief stoppage in drilling while the tool pushes a pad sealing element against the wellbore wall and performs a series of pressure draw down (DD) and buildup (BU) tests to measure formation pressure. The measurements are performed relatively quickly to minimize the chance of differential sticking, especially in long horizontal wells. FPWD has been recently used successfully in detecting heavy/immobile fluids in combination with LWD NMR. In clean carbonates, zones containing immobile high viscous fluids are generally characterized by lost seals, supercharged pressures, and very low mobilities in the range of 0.1-0.2 md/cp.5 Real-time detection of zones with immobile fluids and low permeability allows their avoidance and makes geosteering long horizontal wells into sweet spots possible.
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Pyrolytic Oil Productivity Index.
Pyrolytic Oil Productivity Index (POPI) was developed by Saudi Aramco to provide a quantitative assessment of reservoir quality, productivity, water saturation and tar identification from residual hydrocarbon staining on drill cuttings. Unlike other logging tools, POPI provides a direct assessment of residual hydrocarbons on rock samples, which can be used to assess connectivity with the active fluid system in the reservoir. POPI includes various pyrolysis methods such as assessment of API gravity, the Apparent Saturation Method, and the Volume Organic Matter method. POPI can accurately quantify tar volume over a wide range of concentrations to support real-time application and geosteering horizontal wells .6
Integrating Tar Identifying Technologies Two case studies from a Saudi Arabian field are discussed to demonstrate the successful integration of tar identifying technologies. Both cases are examples of long horizontal water injectors drilled in oil bearing clean carbonate formations. The knowledge of tar zone depth gained from the first well was very well utilized to drill the second well. In both cases, the different tar identifying technologies were effectively used to properly geosteer the wells and achieve the objectives. Case 1.
Well-X is a water injector that was successfully placed real-time away from tar in a clean carbonate reservoir that is both heterogeneous and characterized by an undulating tar mat. Based on the best tar-depth estimation from nearby offset wells, the original plan of Well-X was to enter the reservoir as deep as possible in the low viscosity oil zone but avoid the tar just below it. Figure 4 a and b shows a cartoon of the planned as well as the actual well paths.
Tar / Immobile Oil
Aquifer
Mobile Oil
Tar / Immobile Oil
Aquifer
Mobile Oil
Plan Actual
Figure 4a. Planned well path for Well-X.
Figure 4b. Actual well path after adjusting real-time for tar.
The challenge was to drill a long horizontal section just above the tar without entering into it. The light oil-tar contact was very uncertain. The drilling BHA was equipped with tar indicating technologies such as the LWD NMR, FPWD and a surface POPI unit to real-time analyze the drill cuttings. T2 distribution, NMR derived porosities (free fluids and immovable fluid volumes), formation pressures and mobilities were transmitted real-time along with the conventional logs like gamma ray, density and neutron porosity to identify tar and make quick decisions to change well plan if necessary. Along with the conventional curves, viscosity from NMR and excess bound fluid were also calculated and displayed. As planned, the well entered into the low viscosity zone (zone A) of the reservoir (Figure 6), but with couple of hundred feet into the reservoir, the formation pressure tests were performed and showed pressures indicating supercharged (Track 3) and very low mobilities values (Track 6). The tails of NMR T2 distribution (Track 2) showed a shift towards the left (towards faster relaxation times). These were the first indications of tar, but the shape and position of the T2 distributions are not a unique tar indicator, and could be affected by other factors (pore size reduction, wettability alteration, etc.) as well.
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A
B
C
Good oil: • Excellent agreement between NMR and conventional total porosity
• No excess bound fluid • No supercharged pressure • High mobility
Tar zone: • Deficit in NMR porosity • Presence of excess bound fluid • Shortened T2 • Supercharged pressure • Low mobility
Back into good oil: • Excellent agreement between NMR and conventional total porosity
• No excess bound fluid • No supercharged pressure • High mobility
X1500
X0500
X1000
X2000
X2500
X3000
Reference (ft)
Figure 5. Well-X LWD logs from NMR, FPWD and triple combo tools.
Track 4 of Figure 5 compares the total porosity derived from neutron-density logs (blue curve) with free and bound fluid porosities from NMR shaded in yellow and blue respectively. There is very good agreement between total porosity and NMR porosity in zone A and C. However in zone B, once the T2 distribution shifts towards faster relaxation times, the NMR shows a porosity deficit compared to total porosity, and the computed viscosity (Track 6) indicates high viscous tar. Another clear tar indication comes from the excess bound fluid, which is shown in Track 5 as a black filled curve. These indications proved to be very useful in making decisions in real-time. The well plan was revised to navigate the well out of the tar zone. Once the depth of the tar zone was identified, the rest of the well section was maintained above it, which is clearly indicated by the data from zone C in Figure 5. The benefits of these technologies were clearly visible by a short-term injectivity test after the well was completed which showed a poor injectivity in the tar identified zone (zone B), but a very good injection rate in the low viscosity oil zone (zone C).
Case 2.
Based on the knowledge gained from Well-X about the tar depth, another water injector well, Well-Y, was planned to be drilled and placed above the tar in the low viscosity oil zone. This time it was decided to drop the angle of the well towards the end in an attempt to confirm the presence of tar just below. Figure 6 describes the proposed well plan for Well-Y.
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Tar / Immobile Oil
Aquifer
Mobile Oil
Figure 6. Proposed well path for Well-Y.
The same BHA, employing the tar detection technology, was used in Well-X was utilized in this case as well. As per plan, the well entered into the low viscosity zone (zone A) of the reservoir (Figure 7) which is indicated by high mobilities from FPWD (Track 6), of the late peaks in the NMR T2 distribution (Track 2) and the total porosity from neutron-density overlying the NMR-derived porosity (Track 4).
Good oil: • Excellent agreement between NMR and conventional total porosity especially in the first half of the well
• Negligible excess bound fluid • No supercharged pressure • High mobility
Tar zone: • Deficit in NMR porosity • Presence of excess bound fluid • Shortened T2
A
B
X1500
X0500
X1000
X2000
X2500
X3000
Reference (ft)
Figure 7. Well-Y LWD logs from NMR, FPWD and triple combo tools.
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The well angle was held for a few thousand feet to stay at the same TVD and just before 300 feet close to the total depth, the well was deviated downwards. As the well entered into deeper zones, the NMR T2 distribution shifted towards the left, deficit in NMR porosity was indicated, and excess bound fluid showed an increase. Thus, all indicators confirmed the presence of tar.
Conclusions The case studies prove the effectiveness of integrating NMR, FPWD and POPI technologies in real-time for identifying tar zones in clean carbonates reservoirs.
• In the first case study the tar zone depth was successfully established with the help of tar identifying technologies in a long horizontal injector. It was confirmed by a short term injectivity test which showed extremely low injectivity in the identified tar zone.
• The second case study shows the effective use of the tar depth knowledge from the previous well for drilling a new long horizontal injector deep into the low viscosity zone without entering the tar. The depth of the oil-tar contact was confirmed by tar identifying technologies when drilling deeper into the anticipated tar zone.
References
1. Al-Kaabi, A., Menouar H., Al-Marhoun, M. A., Al-Hashim, H. S.: “Bottom Water Drive in Tarmat Reservoirs,” SPE Reservoir Engineering, May 1988.
2. Akkurt, R., Seifert, D. J., Al-Harbi A., Al-Beaiji, T. M., Kruspe, T., Thern, H., Kroken, A.: “Real Time Detection of Tar in Carbonates Using LWD Triple Combo, NMR and Formation Tester in Highly Deviated Wells,” Paper presented at the SPWLA 49th Annual Logging Symposium, Edinburgh, Scotland, May 25-28, 2008.
3. Akkurt, R., Seifert, D. J., Eyvazzadeh R., Al-Beaiji, T.: “From Molecular Weight and NMR Relaxation to Viscosity: An Innovative Approach for Heavy Oil Viscosity Estimation for Real-Time Applications,” Petrophysics, Vol. 51, No. 2, April 2010
4. Chen, J., Chen, S.: “A Mixing Rule of Self Diffusivities in Methane Hydrocarbon Mixtures and the Determination of GOR and Oil Viscosities from NMR Log Data,” SPE Reservoir Evaluation & Engineering, April 2010.
5. Seifert, D. J., Neuman, P. M., Dossary, S. M., Chew, K., Hahne, U., Bacciarelli, M., Pragt, J.: “Characterization of Arab Formation Carbonates Utilizing Real-time Formation Pressure and Mobility Data,” SPE paper 109902, SPE Annual Technical Conference and Exhibition, Anaheim, California, U.S.A, 11-14 November 2007
6. Al-Salem, K. M., Al-Maliki, S. S., Ahyed, R. A., Jones, P.J., Neumann, P. M.: “Real Time Well Placement above a Tarmat, Leveraging Formation Pressure While Drilling and Pyrolitic Oil Productivity Index Technologies,” SPE paper 113550, Presented at SPE Europe/EAGE Annual Conference and Exhibition held in Rome, Italy, 9-12 2008.
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