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Fracture diagnostic techniques are divided into several groups. Direct far-field methods consists of tiltmeter-fracture-mapping and microseismic-fracture-mapping techniques. These techniques require sophisticated instrumentation embedded in boreholes surrounding the well to be fracture treated. When a hydraulic fracture is created, the expansion of the fracture causes the earth around the fracture to deform. Tiltmeters can be used to measure the deformation and to compute the approximate direction and size of the created fracture.
In most exploration and reservoir seismic surveys, the main objectives are, first, to correctly image the structure in time and depth and, second, to correctly characterize the amplitudes of the reflections. Assuming that the amplitudes are accurately rendered, a host of additional features can be derived and used in interpretation. Collectively, these features are referred to as seismic attributes. The simplest attribute, and the one most widely used, is seismic amplitude, and it is usually reported as the maximum (positive or negative) amplitude value at each sample along a horizon picked from a 3D volume. It is fortunate that, in many cases, the amplitude of reflection corresponds directly to the porosity or to the saturation of the underlying formation.
Traditional methods of monitoring reservoir behavior, including reservoir simulation and history-matching with production rates and pressure, can produce nonunique solutions for reservoir behavior in the interwell regions. In some instances, the uncertainty can be significant, and additional information is needed to optimize production and improve estimates of ultimate recovery. In many cases, the effect of the changing reservoir pressure and/or saturation on seismic data can be used to map the changing pattern of these reservoir properties by obtaining seismic data repeatedly during production of the reservoir. With care, seismic data obtained for other purposes (such as regional exploration) can sometimes be used for time-lapse seismic monitoring, but new data are often obtained from seismic experiments designed particularly to monitor the reservoir. The desire to minimize differences in acquisition parameters between surveys has led, in some cases, to permanent installation of sensors in the oilfield.
Acoustic logging is a subset of borehole-geophysical acoustic techniques. Continuing developments in tool hardware and in interpretation techniques have expanded the utility of these logs in formation evaluation and completion (fracture) design and evaluation. A virtual explosion in the volume of acoustic research conducted over the past 20 years has resulted in significant advances in the fundamental understanding of downhole acoustic measurements. These advances, in turn, have greatly influenced practical logging technology by allowing logging-tool designs to be optimized for specific applications. Acoustic-wave data-acquisition methods cover a broad range of scales from millimeters to hundreds of meters (Figure 1).
As seismic acoustic waves pass through rock, some of their energy will be lost to heat. For tight, hard rocks, this loss can be negligible. However, for most sedimentary rocks, this loss will be significant, particularly on seismic scales. In reality, all rocks are inelastic to some degree. This article discusses the calculations to account for this energy loss.
To extract fluid types or saturations from seismic, crosswell, or borehole sonic data, we need a procedure to model fluid effects on rock velocity and density. Numerous techniques have been developed. However, Gassmann's equations are by far the most widely used relations to calculate seismic velocity changes because of different fluid saturations in reservoirs. The importance of this grows as seismic data are increasingly used for reservoir monitoring. Gassmann's formulation is straightforward, and the simple input parameters typically can be directly measured from logs or assumed based on rock type.
Elastic waves are comprised of compressional (or P-waves) and shear (or S-waves). In compressional waves, the particle motion is in the direction of propagation. In shear waves, the particle motion is perpendicular to the direction of propagation. Understanding the velocity of these waves provide valuable information about the rocks and fluids through which they propagate. Stress strain relationships in rocks considered only the static elastic deformation of materials.
This field produces from a structure that lies above a deep-seated salt dome (salt has been penetrated at 9,000 ft) and has moderate fault density. A large north/south trending fault divides the field into east and west areas. There is hydraulic communication across the fault. Sands were deposited in aeolian, fluvial, and deltaic environments made up primarily of a meandering, distributary flood plain. Reservoirs are moderate to well sorted; grains are fine to very fine with some interbedded shales. There are 21 mapped producing zones separated by shales within the field but in pressure communication outside the productive limits of the field. The original oil column was 400 ft thick and had an associated gas cap one-third the size of the original oil column. Porosity averages 30%, and permeability varies from 10 to 1500 md.
There are several specific differences between exploration geophysics and reservoir geophysics, as the term is usually intended. The differences include: the assumption that well control is available within the area of the geophysical survey; a carefully designed geophysical survey can be conducted at a level of detail that will be useful; some understanding of the rock physics is available for interpretation; 3D seismic (or other geophysical) data can be collected; and geostatistical techniques can be applied to it. The reservoir geophysicist should be familiar with the usefulness and limitations of petrophysical and reservoir-engineering studies and should be able to ask intelligent questions of the experts in those fields. However, the reservoir geophysicist typically is not an expert in those areas and works with the appropriate specialists to interpret the data or to design a new experiment to solve reservoir problems. In exploration, extrapolation of well data from far outside the area of interest is often necessary, and the interpretation is required to cross faults, sequence boundaries, pressure compartments, and other discontinuities that may or may not be recognized.
Both the computation of classical statistical measures (e.g., mean, mode, median, variance, standard deviation, and skewness), and graphic data representation (e.g., histograms and scatter plots) commonly are used to understand the nature of data sets in a scientific investigation--including a reservoir study. A distinguishing characteristic of earth-science data sets (e.g., for petroleum reservoirs), though, is that they contain spatial information, which classical statistical descriptive methods cannot adequately describe. Spatial aspects of the data sets, such as the degree of continuity--or conversely, heterogeneity--and directionality are very important in developing a reservoir model. Analysis of spatially rich data is within the domain of geostatistics (spatial statistics), but a foundation in classical statistics and probability is prerequisite to understanding geostatistical concepts. Sampling also has proved invaluable in thousands of studies, but it, too, can lead to statistical insufficiencies and biases.