Abstract Seismic reflections come from interfaces where the acoustic properties of the rocks change, and this fact is the basis of our understanding of the nature of seismic data. Acoustic impedance of a rock layer is the product of the density and the velocity of that layer, and strictly a reflection is generated by a contrast in acoustic impedance. In fact impedance and lithology normally follow each other, so that impedance boundaries and lithologic boundaries normally concur. Consider a sand encased in shale, perhaps the most common situation forming a hydrocarbon reservoir. The shale-sand interface at the top generates a reflection, and the sand-shale interface at the base generates a reflection (Figure 1-1 ). Thus a sand has a reflection from the top and another from the base. These two reflections should be considered together in all studies of the reservoir sand. At one location the sands normally have one impedance and the shales have another impedance. (Typically, sands have a lower impedance than shales in younger rocks and a higher impedance than shales in older rocks.) Thus the interfaces at top and base of a sand reservoir will almost always have impedance contrasts in the opposite sense. The sense of the impedance contrast determines the polarity of the seismic reflection, so that the top and base reflections for a sand reservoir encased in shale are opposite polarity from each other. This is a very significant piece of information used in the identification of reservoir reflections. Numerous figures in this book illustrate the pairing of top and base reflections — for example, Figure 1-1 many figures in Chapters 2 and 5 . Tying of geologic data and seismic data together involves some knowledge of velocity, but the depth-to-time tie is not sufficient. We must identify seismic reflections on the basis of the character expected from the geologic interfaces and the fact that the layer of interest will normally have a top reflection and a base reflection. Consideration of the top and base reflections together involves the topics of natural pairing, choice of color schemes, data phase, data polarity, seismic resolution, and tuning, all of which are subjects of this book.

Abstract “The total quantity of information recorded on a typical seismic line is enormous. It is virtually impossible to present all this information to the user in a comprehensible form.” This quotation from Balch (1971) is even more true today than it was in 1971 and color has become an important contributor to the problem’s solution. The human eye is very sensitive to color and the seismic interpreter can make use of this sensitivity in several ways. Taner and Sheriff (1977) and Lindseth (1979) were among the first to present color sections which demonstrated the additional information color can convey. Of equal importance is the increased optical dynamic range of a color section compared to its black and white variable area/wiggle trace equivalent. Both these properties are of great importance in stratigraphic interpretation.

Abstract The 3-D seismic interpreter works with a volume of data. Normally this is done by studying some of each of the three orthogonal slices through the volume. This chapter explores the unique contribution of the horizontal section to structural interpretation. The interpreter of structure needs to be able to judge when to use horizontal sections and when to use vertical ones in the course of an overall interpretive project. Figure 3-1 demonstrates the conceptual relationship between a volume of subsurface rock and a volume of seismic data. Consider the diagram first to represent subsur-face rocks and the gray surface to be a bedding plane. The two visible vertical faces of the rectangular solid show the two dip components of the plane; the horizontal face shows the strike of the plane. Now consider the rectangular solid of Figure 3-1 to be the equivalent volume of seismic data. The gray plane is now a dipping reflection and its intersections with the three orthogonal faces of the solid show the two components of dip and the strike as before. Hence the attitude of a reflection on a horizontal section indicates directly the strike of the reflecting surface. This is the fundamental property of the horizontal section from which all its unique interpretive value derives.

Abstract Where a vertical seismic section intersects a stratigraphic feature the interpreter can normally find a small amplitude or character anomaly. The expression of a sand-filled channel or bar, for example, is therefore normally so subtle that it takes a considerable amount of interpretive skill to detect it. In contrast, a horizontal section reveals the spatial extent of an anomaly. The interpreter can thus observe characteristic shape and relate what he sees to geologic experience. A shape or pattern which is unrelated to structure may prove to be interpretable as a depositional, erosional, lithologic or other feature of significance. Klein (1985) and Broussard (1975) , among others, have provided depositional models on which the interpreter can base his recognition of depositional features. The study of horizontal sections and horizon slices can provide a bird’s-eye view of ancient stratigraphy, analogous to the view of modern stratigraphy obtained out of an airplane window. Figure 4-1 shows five adjacent vertical seismic sections from a small 3-D survey in the Williston basin of North Dakota. Note that the reflections indicate largely flat-lying beds. At 1.8 seconds there is a very slight draping of reflections which is only just discernible. Figure 4-2 shows two single-polarity horizontal sections superimposed on each other. The data from both levels reveal the same almost circular shape. This is the outline of a carbonate buildup measuring approximately one kilometer in diameter.

Abstract Figure 5-1 shows a bright spot presented by Tegland (1973) . This was one of the early examples studied and was observable because amplitude had been preserved in seismic processing. In earlier years, when records were normally made with automatic gain control, there was little opportunity for studying amplitudes. The bright spot of Figure 5-1 is actually a very good one for its era because it also shows a flat spot, presumably a fluid contact reflection. The flat spot terminates laterally at the same points as does the bright spot; we would consider this a simple form of bright spot validation, increasing the interpreter’s confidence that the anomaly indicates the presence of hydrocarbons. With the improvements in seismic processing over two decades, we can now consider polarity and phase as well as amplitude and spatial extent. Frequency, velocity, amplitude/offset and shear wave information can also help in the positive identification of hydrocarbon indicators. These are all subjects of this chapter and the direct observation of hydrocarbon fluids is now very widespread. Most direct hydrocarbon indication relates to gas rather than oil reservoirs as the effect on acoustic properties of gas in the pore space is significantly greater than oil.Figure 5-2 (derived from Gardner, Gardner, and Gregory, 1974) summarizes the different effects of gas and oil and shows that the effect of either diminishes with depth.

Abstract Widess (1973) demonstrated the interaction of closely-spaced reflections. In his classic paper, “How thin is a thin bed?,” he discussed the effect of bed thickness on seismic signature. For a bed thickness of the order of a seismic wavelength or greater there is little or no interference between the wavelets from the top and the bottom of the bed and each is recorded without modification. For thinner beds these wavelets interfere both constructively and destructively. Considering wavelets of opposite polarity, the amplitude of the composite wavelet reaches a maximum for a bed thickness of one-quarter wavelength (one-half period) and this is known as the tuning thickness. For beds thinner than this the shape of the composite wavelet stays the same but its amplitude decreases. Clearly, the bed thicknesses at which these phenomena occur depend on the shape of the wavelet in the data and hence on its frequency content. These tuning phenomena are of considerable importance to the stratigraphic interpreter. They must be recognized as effects of bed geometry as opposed to variations in the acoustic properties of the medium. Figure 6-1 shows a sedimentary pod. As the reflections from the top and the base come together (within the black square) the amplitude abruptly increases; this is interpreted as tuning between the top and base reflections.

Abstract Reservoir evaluation, reservoir characterization or reservoir property mapping is an important use of 3-D seismic data. As presented here it is an extension of reservoir reflection identification (Chapter 5) , horizon slicing techniques (Chapter 4) and tuning phenomena (Chapter 6) . Further issues on reservoir evaluation follow in Chapter 8 .

Since the early to mid-1980s, inversion has been in discussion. Inversion is defined by Sheriff in his dictionary of geophysics terms as “Deriving from field data a model to describe the subsurface that is consistent with the data”( Sheriff, 2002 , p. 194). My first exposure was at Amoco when I heard this topic discussed by Roy Lindseth. An excellent history of the topic is given in Lindseth (1979) . The term inversion has always seemed to mean different things to different people. It also seemed to evoke very strong comments based on individuals’ experiences on the topic. I was recently told that a “constrained sparse-spike inversion algorithm” was simply nothing more than a phase rotation of the seismic. When I mentioned the parameters that went into this type of algorithm, the individual did not want to discuss it because it did not support his argument against utilizing the process. I am forever amazed at how much confusion there still is and at how people can be so completely confused in their very definitive statements. In 2000, I wrote an article in the Society of Exploration Geophysicists’ The Leading Edge in an effort to present a guide to the interpreters who use inverted data ( Latimer et al., 2000) . A lot has happened since 2000, and it is time to update the interpreter community with added details and further explanations, which are featured in this chapter. I will expand the discussion from simply post-stack seismic-trace inversion to include pre-stack data and geostatistical inversion. I will provide a description of terminology and again a basis for comparison and usage of acoustic-impedance inversion products, and I will give the interpreter a methodology for quality control and interpretation of inverted data. I still contend, as I did in 2000, that the first and foremost prerequisite in doing any type of inversion is to have the absolute best seismic processing completed prior to attempting an inversion. I will show, however, that a post-stack inverted data set may help you determine whether the data should be reprocessed, thereby indicating that it can sometimes also be used as a screening tool for further work.

Abstract Depth conversion concerns the seismic interpreter because seismic measurements are made in time, but the wells based on a seismic interpretation are drilled in depth. The depth conversion can now be carried out as part of the data processing, but this depth imaging is only done in special circumstances. Historically, geophysical interpreters have relied more and more on automatic data processing to prepare the data for interpretation. The way this has occurred for depth conversion is shown in Figure 10-1 . Depth imaging is used when the velocity distribution and structural complexity are such that the time image of the subsurface does not permit the interpreter to understand the geology (Figure 10-2) . Depth imaging is difficult, expensive and never completely accurate. The most accurate depth imaging uses pre-stack depth migration of the 3-D seismic data volume, a computationally intensive task which is critically dependent on an accurate velocity field. The velocity field cannot be known until the geological structure is known, and the geological structure cannot be known until the seismic volume has been migrated. Consequently, the depth imaging process usually involves iteration.