New Downhole-Fluid-Analysis Tool for Improved Reservoir Characterization
- Chengli Dong (Schlumberger) | Michael D. O'Keefe (Schlumberger) | Hani Elshahawi (Shell) | Mohamed Hashem (Shell) | Stephen M. Williams (StatoilHydro) | Dag Stensland (ENI Norge) | Peter S. Hegeman (Schlumberger) | Ricardo R. Vasques (Schlumberger) | Toru Terabayashi (Schlumberger) | Oliver C. Mullins (Schlumberger) | Eric Donzier (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- December 2008
- Document Type
- Journal Paper
- 1,107 - 1,116
- 2008. Society of Petroleum Engineers
- 5.2.2 Fluid Modeling, Equations of State, 4.3.3 Aspaltenes, 5.2 Fluid Characterization, 3.3.6 Integrated Modeling, 4.2.3 Materials and Corrosion, 4.1.2 Separation and Treating, 5.1.1 Exploration, Development, Structural Geology, 4.1.9 Tanks and storage systems, 5.2 Reservoir Fluid Dynamics, 4.1.5 Processing Equipment, 1.11 Drilling Fluids and Materials, 5.3.2 Multiphase Flow, 5.6.1 Open hole/cased hole log analysis, 5.8.8 Gas-condensate reservoirs, 4.6 Natural Gas, 4.2 Pipelines, Flowlines and Risers, 5.2.1 Phase Behavior and PVT Measurements, 5.1 Reservoir Characterisation, 5.6.4 Drillstem/Well Testing
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Downhole fluid analysis (DFA) has emerged as a key technique for characterizing the distribution of reservoir-fluid properties and determining zonal connectivity across the reservoir. Information from profiling the reservoir fluids enables sealing barriers to be proved and compositional grading to be quantified; this information cannot be obtained from conventional wireline logs. The DFA technique has been based largely on optical spectroscopy, which can provide estimates of filtrate contamination, gas/oil ratio (GOR), pH of formation water, and a hydrocarbon composition in four groups: methane (C1), ethane to pentane (C2-5), hexane and heavier hydrocarbons (C6+), and carbon dioxide (CO2). For single-phase assurance, it is possible to detect gas liberation (bubblepoint) or liquid dropout (dewpoint) while pumping reservoir fluid to the wellbore, before filling a sample bottle.
In this paper, a new DFA tool is introduced that substantially increases the accuracy of these measurements. The tool uses a grating spectrometer in combination with a filter-array spectrometer. The range of compositional information is extended from four groups to five groups: C1, ethane (C2), propane to pentane (C3-5), C6+, and CO2. These spectrometers, together with improved compositional algorithms, now make possible a quantitative analysis of reservoir fluid with greater accuracy and repeatability. This accuracy enables comparison of fluid properties between wells for the first time, thus extending the application of fluid profiling from a single-well to a multiwall basis. Field-based fluid characterization is now possible.
In addition, a new measurement is introduced--in-situ density of reservoir fluid. Measuring this property downhole at reservoir conditions of pressure and temperature provides important advantages over surface measurements. The density sensor is combined in a package that includes the optical spectrometers and measurements of fluid resistivity, pressure, temperature, and fluorescence that all play a vital role in determining the exact nature of the reservoir fluid.
Extensive tests at a pressure/volume/temperature (PVT) laboratory are presented to illustrate sensor response in a large number of live-fluid samples. These tests of known fluid compositions were conducted under pressurized and heated conditions to simulate reservoir conditions. In addition, several field examples are presented to illustrate applicability in different environments.
Reservoir-fluid samples collected at the early stage of exploration and development provide vital information for reservoir evaluation and management. Reservoir-fluid properties, such as hydrocarbon composition, GOR, CO2 content, pH, density, viscosity, and PVT behavior are key inputs for surface-facility design and optimization of production strategies. Formation-tester tools have proved to be an effective way to obtain reservoir-fluid samples for PVT analysis. Conventional reservoir-fluid analysis is conducted in a PVT laboratory, and it usually takes a long time (months) before the results become available. Also, miscible contamination of a fluid sample by drilling-mud filtrate reduces the utility of the sample for subsequent fluid analyses. However, the amount of filtrate contamination can be reduced substantially by use of focused-sampling cleanup introduced recently in the next-generation wireline formation testers (O'Keefe et al. 2008).
DFA tools provide results in real time and at reservoir conditions. Current DFA techniques use absorption spectroscopy of reservoir fluids in the visible-to-near-infrared (NIR) range. The formation-fluid spectra are obtained in real time, and fluid composition is derived from the spectra on the basis of C1, C2-5, C6+, and CO2; then, GOR of the fluid is estimated from the derived composition (Betancourt et al. 2004; Fujisawa et al. 2002; Dong et al. 2006; Elshahawi et al. 2004; Fujisawa et al. 2008; Mullins et al. 2001; Smits et al. 1995). Additionally, from the differences in absorption spectrum between reservoir fluid and filtrate of oil-based mud (OBM) or water-based mud (WBM), fluid-sample contamination from the drilling fluid is estimated (Mullins et al. 2000; Fadnes et al. 2001).
With the DFA technique, reservoir-fluid samples are analyzed before they are taken, and the quality of fluid samples is improved substantially. The sampling process is optimized in terms of where and when to sample and how many samples to take. Reservoir-fluid characterization from fluid-profiling methods often reveals fluid compositional grading in different zones, and it also helps to identify reservoir compartmentalization (Venkataramanan et al. 2008).
A next-generation tool has been developed to improve the DFA technique. This DFA tool includes new hardware that provides more-accurate and -detailed spectra, compared to the current DFA tools, and includes new methods of deriving fluid composition and GOR from optical spectroscopy. Furthermore, the new DFA tool includes a vibrating sensor for direct measurement of fluid density and, in certain environments, viscosity. The new DFA tool provides reservoir-fluid characterization that is significantly more accurate and comprehensive compared to the current DFA technology.
|File Size||3 MB||Number of Pages||10|
Betancourt, S.S., Fujisawa, G., Mullins, O.C., Eriksen, K.O., Dong, C., Pop,J., and Carnegie, A. 2004. Exploration Applications of DownholeMeasurement of Crude Oil Composition and Fluorescence. Paper SPE 87011presented at the SPE Asia Pacific Conference on Integrated Modelling for AssetManagement, Kuala Lumpur, 29-30 March. DOI: 10.2118/87011-MS.
Del Campo, C., Dong, C., Vasques, R., Hegeman, P., and Yamate, T. 2006. Advances in Fluid Sampling WithFormation Testers for Offshore Exploration. Paper OTC 18201 presented atthe Offshore Technology Conference, Houston, 1-4 May.
Dong, C., Del Campo, C., Vasques, R., Hegeman, P., and Matsumoto, N. 2005.Formation testing innovations for fluid sampling. Paper presented at the DeepOffshore Technology International Conference and Exhibition, Vitoria, Brazil,8-10 November.
Dong, C., Hegeman, P.S., Carnegie, A., and Elshahawi, H. 2006. Downhole Measurement of Methane andGOR Content in Formation Fluid Samples. SPEREE 9 (1): 7-14.SPE-81481-PA. DOI: 10.2118/81481-PA.
Elshahawi, H., Hashem, M., Dong, C., Hegeman, P., Mullins, O.C., Fujisawa,G., and Betancourt, S. 2004. In-situ Characterization of FormationFluid Samples--Case Studies. Paper SPE 90932 presented at the SPE AnnualTechnical Conference and Exhibition, Houston, 26-29 September. DOI:10.2118/90932-MS.
Fadnes, F.H., Irvin-Fortescue, J., Williams, S., Mullins, O.C., and VanDusen, A. 2001. Optimization ofWireline Sample Quality by Real-Time Analysis of Oil-Based MudContamination--Examples from North Sea Operations. Paper SPE 71736presented at the SPE Annual Technical Conference and Exhibition, New Orleans,30 September-3 October. DOI: 10.2118/71736-MS.
Fujisawa, G., van Agthoven, M.A., Jenet, F., Rabbito, P., and Mullins, O.C.2002. Near-InfraredCompositional Analysis of Gas and Condensate Reservoir Fluids at ElevatedPressures and Temperatures. Applied Spectroscopy 56 (12):1615-1620. DOI: 10.1366/000370202321116101.
Fujisawa, G., Betancourt, S.S., Mullins, O.C., Torgersen, T., O'Keefe, M.,Terabayashi, T., Dong, C., and Eriksen, K.O. 2008. Hydrocarbon Compositional GradientRevealed by In-Situ Optical Spectroscopy. SPEREE 11 (2):233-237. SPE-89704-PA. DOI: 10.2118/89704-MS.
Mullins, O.C., Schroer, J., and Beck, G.F. 2000. Real-time quantification ofOBM filtrate contamination during open hole wireline sampling by opticalspectroscopy. Trans., SPWLA 41st Annual Logging Symposium, Dallas, 4-7June, Paper SS, 1-10.
Mullins, O.C., Beck, G.F., Cribbs, M.E., Terabayashi, T., and Kegasawa, K.2001. Downhole determination of GOR on single-phase fluids by opticalspectroscopy. Trans., SPWLA 42nd Annual Logging Symposium, Houston,17-20 June, Paper M.
O'Keefe, M., Eriksen, K.O., Williams, S., Stensland, D., and Vasques, R.2008. Focused Sampling ofReservoir Fluids Achieves Undetectable Levels of Contamination.SPEREE 11 (2): 205-218. SPE-101084-PA. DOI:10.2118/101084-PA.
Raghuraman, B., O'Keefe, M., Eriksen, K.O., Tau, L.A., Vikane, O.,Gustavson, JG., and Indo, K. 2007. Real-Time Downhole pH MeasurementUsing Optical Spectroscopy. SPEREE 10 (3): 302-311.SPE-93057-PA. DOI: 10.2118/93057-PA.
Smits, A.R., Fincher, D.V., Nishida, K., Mullins, O.C., Schroeder, R.J., andYamate, T. 1995. In-Situ OpticalFluid Analysis as an Aid to Wireline Formation Sampling. SPEFE10 (2): 91-98. SPE-26496-PA. DOI: 10.2118/26496-PA.
Venkataramanan, L., Elshahawi, H., McKinney, D., Flannery, M., Hashem, M.,and Mullins, O.C. 2008. DownholeFluid Analysis and Fluid-Comparison Algorithm as Aid to ReservoirCharacterization. SPEREE 11 (3): 535-543. SPE-100937-PA. DOI:10.2118/100937-PA.