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Tight gas is the term commonly used to refer to low permeability reservoirs that produce mainly dry natural gas. Many of the low permeability reservoirs that have been developed in the past are sandstone, but significant quantities of gas are also produced from low permeability carbonates, shales, and coal seams. Production of gas from coal seams is covered in a separate chapter in this handbook. In this chapter, production of gas from tight sandstones is the predominant theme. However, much of the same technology applies to tight carbonate and to gas shale reservoirs.
- North America > United States > Texas (1.00)
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- North America > United States > Colorado (0.67)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.69)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.68)
- North America > United States > Texas > Travis Peak Formation (0.99)
- North America > United States > Texas > East Texas Salt Basin > Whelan Lease > Waskom Field > Lowe Paluxy Formation (0.99)
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- Geology > Mineral (0.96)
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- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.68)
- South America > Ecuador > Pastaza > Oriente Basin > Block 10 > Villano Field (0.99)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
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- Well Drilling > Drilling Operations > Coring, fishing (1.00)
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In making the petrophysical calculations of lithology, net pay, porosity, water saturation, and permeability at the reservoir level, the development of a complete petrophysical database is the critical first step. This section describes the requirements for creating such a database before making any of these calculations. The topic is divided into four parts: inventory of existing petrophysical data; evaluation of the quality of existing data; conditioning the data for reservoir parameter calculations; and acquisition of additional petrophysical data, where needed. The overall goal of developing the petrophysical database is to use as much valid data as possible to develop the best standard from which to make the calculations of the petrophysical parameters. Inventory of Existing Petrophysical Data To start the petrophysical calculations, the data that have been gathered previously from various wellbores throughout the reservoir must be identified, organized, and put into electronic form for future calculations.
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- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
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- Geology > Mineral > Silicate > Phyllosilicate (0.71)
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- Geophysics > Borehole Geophysics (1.00)
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- North America > United States > Wyoming > Greater Green River Basin > Carter Creek Field (0.99)
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Summary. The methods available for the interpretation of well logs in shaly sandstones are numerous. Deciding which methods to apply in a given area or formation is often difficult. A cation-exchange-capacity (CEC) correlation is presented for the Mesaverde group of the Uinta basin, Utah. Three porosity estimators are compared with core porosities. Nine water-saturation estimators are compared with Waxman-Smits water saturations. Introduction Statement of the Problem. Many methods of determining shale volume, porosity, and water saturation from well-log interpretations have been proposed. These methods are based on empirical relations and simplified models of the reservoir rock. For a marginal well, the decisions made by the analyst will be dictated by the choice of interpretation methods. This study is limited to methods for shaly-sand interpretation that are in common use or have been recently proposed and that are applicable to the Mesaverde group of the Uinta basin, Utah. Many of these techniques were developed in other areas, but are also valid in the Uinta basin. The well-log interpretation techniques are compared by use of one set of data from the Mesaverde group. Core data available from the Mesaverde group are used as a basis for comparison of three techniques for prediction of porosity. The Waxman-Smits method for determination of water saturation in shaly sands was selected for comparison of nine other techniques. The Waxman-Smits method has been used as the water-saturation determination method of choice when CEC data were available. A correlation of CEC with the gamma ray index is used to determine the Waxman-Smits water saturations. Formation water resistivity is difficult to determine in the Mesaverde group. The saltwater mud used in wells attenuates the spontaneous potential (SP), and thin beds, clay, low permeability. and variable-invasion profiles distort the SP curve, therefore, the SP is not available for water-resistivity determination. The apparent water-resistivity methods and apparent formation-resistivity factor vs. deep-resistivity crossplots generally fail because a clean, 100% water-saturated interval does not exist. The formation water resistivities that use these techniques are incorrect. Produced water samples and drillstem test samples are often contaminated by drilling fluids and fracturing fluids. Also, the formation fluid may change in character significantly with depth because of temperature, pressure, and the effects of diagenesis. In spite of these difficulties, pressure, and the effects of diagenesis. In spite of these difficulties, the formation water resistivity derived from the produced water is treated as a constant at formation temperature (0.15 omega.m). The conductivity of shale is normally chosen from a nearby shale, and it is assumed that the adjacent shale has the same characteristics as the shale in the reservoir rock in the zone of interest. Often, a technique requires a clay resistivity (resistivity of the clay minerals only). Clay conductivity is associated with CEC. CEC values were found experimentally from core samples. Correlations between CEC values and log parameters must be found to apply CEC values to the well-log interpretation. The log parameters that are generally chosen are the natural gamma ray and the potassium content. The gamma ray appears to give better results. Johnson and Linke, working in the Mackenzie delta area of the Northwest Territories, Canada, found the following relationship on the basis of environmentally corrected gamma ray count ( ): (1) The values of the gamma ray count in clean sand and shale in this region were 48 and 118 API gamma ray units, respectively. Rosepiler, working with data from the Cotton Valley region of cast Texas, reported the following relationship: (2) The clean and shale gamma ray counts were about 4 and 94, respectively. The correlation for the Mesaverde developed from this work is(3) This CEC was predicted by regression analysis of nine data points from cores with the wet chemistry method. The independent variable was the gamma ray index, Iy, based on well-log gamma ray values. This regression analysis yielded a correlation coefficient of 0.9272. Shale-Volume Determination Shale-volume estimators are mathematical relationships that (with one or more well-log-derived properties) give the shale fraction of the reservoir rock. The estimator should yield a value of zero in a clean sandstone and one in a shale. The most common methods use the SP, natural gamma ray, and thorium and potassium curves from the spectral gamma ray. When more than one indicator of shale volume is used, the common practice is to use the least value of the shale volume. The Mesaverde presents handicaps that limit the useful application of most of these techniques. A good SP is not available because salt-based mud is required to prevent the Wasatch (a producible sand above the Mesaverde) expandable layer clays from imbibing fresh water. The gamma ray index, I, is a simple linear estimation of shale volume. (4) SPEFE, P. 178
- North America > United States > Wyoming > Uinta Basin (0.99)
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- North America > Canada > Northwest Territories > Beaufort-Mackenzie Basin > Mackenzie Delta (0.98)
Resistivity logging is an important branch of well logging. Essentially, it is the recording, in uncased (or, recently, even cased) sections of a borehole, of the resistivities (or their reciprocals, the conductivities) of the subsurface formations, generally along with the spontaneous potentials (SPs) generated in the borehole. This recording is of immediate value for geological correlation of the strata and detection and quantitative evaluation of possibly productive horizons. The information derived from the logs may be supplemented by cores (whole core or sidewall samples of the formations taken from the wall of the hole). As will be explained later, several types of resistivity measuring systems are used that have been designed to obtain the greatest possible information under diverse conditions (e.g., induction devices, laterolog, microresistivity devices, and borehole-imaging devices). Many service companies offer resistivity-logging services, and most offer a Web-based catalog that describes each service.
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- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.67)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (1.00)
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- Europe > Netherlands > Groningen > Southern North Sea - Anglo Dutch Basin > Groningen License > Groningen Field > Upper Rotliegend Formation (0.99)
- Europe > Netherlands > Groningen > Southern North Sea - Anglo Dutch Basin > Groningen License > Groningen Field > Limburg Formation (0.99)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.98)
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