Dolomite Perspectives on a Perplexing Mineral
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03 dolomite perspectives on a perplexing mineral
Stratigraphic Traps I. Tulsa:
American Association of Petroleum Geologists, AAPG Treatise of Petroleum Geology, Atlas of Oil and Gas Fields (1990): 1–37. 39. Land LS: “Failure to Precipitate Dolomite at 25°C from Dilute Solution Despite 1000-Fold Oversaturation After 32 Years,” Aquatic Geochemistry 4, nos. 3–4 (September 1998): 361–368. 40. Vasconcelos C and McKenzie JA: “Microbial Mediation of Modern Dolomite Precipitation and Diagenesis Under Anoxic Conditions (Lagoa Vermelha, Rio de Janeiro, Brazil),” Journal of Sedimentary Research 67, no. 3 (May 1997): 378–390. 41. Sánchez-Román M, Vasconcelos C, Schmid T, Dittrich M, McKenzie JA, Zenobi R and Rivadeneyra MA: “Aerobic Microbial Dolomite at the Nanometer Scale: Implications for the Geologic Record,” Geology 36, no. 11 (November 2008): 879–882. 42. Vasconcelos C, McKenzie JA, Warthmann R and Bernasconi SM: “Calibration of the δ 18 O Paleo- thermometer for Dolomite Precipitated in Microbial Cultures and Natural Environments,” Geology 33, no. 4 (April 2005): 317–320. 43. Roberts JA, Bennett PC, González LA, Macpherson GL and Milliken KL: “Microbial Precipitation of Dolomite in Methanogenic Groundwater,” Geology 32, no. 4 (April 2004): 277–280. 44. Ramamoorthy R, Boyd A, Neville TJ, Seleznev N, Sun H, Flaum C and Ma J: “A New Workflow for Petrophysical and Textural Evaluation of Carbonate Reservoirs,” Transactions of the SPWLA 49th Annual Logging Symposium, Edinburgh, Scotland, May 25–28, 2008, paper B. > Carbonate Advisor sequential workflow. The first step incorporates results from tools that provide lithology and porosity information: spectroscopy, density, thermal neutron, epithermal neutron, photoelectric factor, NMR and gamma ray. The data are examined by petrophysicists and serve as inputs to the next step, which involves evaluation of the pore system and permeability using NMR T 2 distribution or image logs. Next, relative permeability and saturation are obtained from array laterolog or array induction resistivity measurements. Also, core data, such as grain density, porosity and permeability, can be added to the analysis. MattV_ORAUT09_Fig_12 Total porosity, vol % 10 5 10 4 10 3 10 2 10 1 r= 0.99 r= 0.99 10 0 10 -1 Permeability , md 10 5 10 4 10 3 10 2 10 1 10 0 10 -1 0 5 10 15 20 25 30 Permeability , md r= 0.99 A Planar-s dolomite Planar-e dolomite B Nonplanar dolomite Spectroscopy Density Thermal neutron Epithermal neutron Photoelectric factor NMR Gamma ray Lithology and porosity Core data NMR T 2 distribution Image log Laterolog resistivity Induction resistivity Grain density Porosity Permeability Pore system and permeability Relative permeability and saturation 26678schD5R1.indd 10 11/5/09 3:53 PM 42 Oilfield Review and dolomite, can be a rather convoluted pro- cess. Neutron porosity measurements must be corrected for the rock matrix. If the matrix con- tains only dolomite or only calcite, the porosity transform is fairly simple. But if the rock contains a mixture of both minerals, then the cor- rect proportions of each must be determined to accurately calculate porosity values. Matrix complexity also affects the computa- tion of density porosity because the equation used to convert porosity from bulk density mea- surements requires matrix density as an input. Should the rock be a mix of dolomite and calcite, the porosity calculations will be incorrect unless an accurate matrix density is obtained. Thus, underestimating or ignoring the presence of dolomite can lead to low computed porosity val- ues that mask potentially productive zones. In some cases, calcite and dolomite can be readily distinguished using PEF data from a Litho-Density tool. 45 The PEF matrix value for pure sandstone is 1.81; for dolomite it is 3.14 and for limestone it is 5.08. From the PEF measure- ment, the percentage of dolomite can be directly calculated if the matrix contains only two miner- als; unfortunately, rocks often contain a mixture of minerals. Adding to the complexity is the fact that even small concentrations of relatively com- mon minerals, such as siderite (with a PEF of 14.7), pyrite (with its PEF of 16.97) or anhydrite (with a PEF of 5.03), distort the measured PEF values and shift the value toward calcite. There are too many unknowns in this case to determine the matrix type and the matrix porosity from a standard logging suite. An additional problem with using PEF for lithology determination is the effect of barite, which is commonly added as a weighting material to drilling mud systems. Barite, with its PEF of 266.82, overwhelms other PEF measurements in these mud systems. The ECS elemental capture spectroscopy tool can help to fill some of the gaps in the interpreta- tion process. Neutron capture spectroscopy mea- sures elemental yields of minerals found in the formation. Recent advances in elemental capture spectroscopy have resulted in improved magne- sium yield measurements to help petrophysicists quantify the amount of dolomite and other miner- als contained in reservoir rocks. ECS measure- ments also provide yields of calcium and sulfur, which are critical for most carbonate lithology determination. In addition, ECS spectroscopy data provide relative yields of elements such as iron, silicon, barium, hydrogen and chlorine. ECS data thus reduce uncertainty in porosity mea- surements derived from basic logging suites. Pore geometry comes into play when evaluat- ing reservoir quality and fluid-flow properties. For the Carbonate Advisor system, the pores are parti- tioned into different types based on pore-throat size. Partitioning is based on NMR transverse relaxation time (T 2 ) distributions augmented by borehole images. Even though NMR is sensitive to pore-body size distribution, the Carbonate Advisor system calibrates the results to appear as pore- throat size distribution. Two cutoffs are applied to T 2 distributions relating relaxation time to pore- size distribution (above left) . The short cutoff defines the microporosity fraction, and the long cutoff defines the macropo- rosity fraction, while the mesoporosity fraction falls between the two. The macroporosity compo- nent is also determined from borehole images by converting the resistivity image into a porosity image and extracting the fraction of large pores present. From the three porosity partitions, eight petrophysical pore system classes are identified. Matrix permeability is also estimated using transforms optimized for each pore class. Permeability estimates can be validated or cali- brated using data from formation testing tools or core measurements. Simultaneous solutions of saturation and rel- ative permeability are obtained through forward modeling. The full model accounts for radial vari- ations in resistivity caused by the distribution of drilling fluids that invaded the formation, which influences resistivity tool response. Both array induction and array laterolog measurements can be used for the analysis. With their multiple depths of investigation, the resistivity tools can accurately characterize the invasion front, which is inverted to determine imbibition relative- permeability curves. The saturation front and salinity front are simultaneously solved to deter- mine fractional flow, relative permeability versus saturation and true formation resistivity. The Carbonate Advisor system was recently put to the test in a reservoir in northern Kuwait. Reservoir evaluation in this area can be compli- cated by drilling fluids weighted with barite, used to increase drilling safety in fields known for high concentrations of hydrogen sulfide and high res- ervoir pressures. 46 Geoscientists with the opera- tor Kuwait Oil Company (KOC) found that zones of improved porosity and permeability were asso- ciated with dolomitization in this field. The quan- tification of dolomite content was therefore important in classifying reservoir quality. However, the estimation of dolomite content from conventional measurements can be hindered by a variety of factors, such as barite mud effects, complex lithologies and sensitivity of logging tool measurements to dolomite, as well as differences in each tool’s vertical resolution and depth of investigation. To overcome these formation evalua- tion challenges, an ECS tool was used to obtain elemental relative yields for mineralogy computa- tion. Magnesium measured by this tool was a key element for dolomite quantification in this com- plex reservoir. The CMR combinable magnetic resonance tool was also run to obtain pore geome- try information. The Carbonate Advisor system provided formation evaluation results that closely agree with core data (next page) . > Pore geometries. Total porosity ( top) can be divided into different types of pores based on NMR and image log data. Micropores, with pore-throat diameters less than 0.5 μm, usually contain mostly irreducible water and little hydrocarbon. Mesopores, with pore-throat diameters between 0.5 and 5 μm, may contain significant amounts of oil or gas in pores above the free-water level (FWL). Macropores, with throats measuring more than 5 μm in diameter, are responsible for prolific production rates in many carbonate reservoirs but often provide pathways for early water breakthrough, leaving considerable gas and oil behind in the mesopores above the FWL. The three different types of pores can be further divided into eight pore system classes ( bottom). MattV_ORAUT09_Fig_13 Total porosity Micro- porosity All pores < 50 to 100 µm have the same T 2 Blind to pores smaller than tool buttons 100% macroporosity 100% microporosity 100% mesoporosity Image response Nonvug porosity Vug porosity NMR response φ for distribution < short Download 2.33 Mb. Do'stlaringiz bilan baham: |
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