Fred Hilterman

Fluid‐property discrimination with AVO: A Biot‐Gassmann perspective

This analysis draws together basic rock physics, amplitude variations with offset (AVO), and seismic amplitude inversion to discuss how fluid‐factor discrimination can be performed using prestack seismic data. From both Biot and Gassmann theories for porous, fluid‐saturated rocks, a general formula is first derived for fluid‐factor discrimination given that both the P and S impedances are available. In essence, the two impedances are transformed so that they better differentiate between the fluid and rock matrix of the porous medium. This formula provides a more sensitive discriminator of the pore‐fluid saturant than the acoustic impedance and is especially applicable in hard‐rock environments. The formulation can be expressed with either the Lame constants and density, or the bulk and shear moduli and density. Numerical and well‐log examples illustrate the applicability of this approach. AVO inversion results are then incorporated to show how this method can be implemented using prestack seismic data. Fi...

THREE‐DIMENSIONAL SEISMIC MODELING

Record sections from three‐dimensional acoustic models often contain diffracted events not predictable by classical raypath theory. Several observed and calculated record sections from models of typical geologic structures such as synclines, anticlines, and faults verify this diffraction phenomenon. A careful interpretation of the character and moveout of these diffracted events is required to delineate certain portions of the geologic structures. A far‐field approximation of the retarded potential equation is suitable for direct time‐domain evaluation and is used to synthesize the calculated sections. The excellent comparisons between the calculated and observed record sections suggest that the mathematical modeling technique can be a useful tool for enhancing field interpretations.

Amplitudes of seismic waves; a quick look

A form of Kirchhoff’s wave equation is presented which is useful to the geophysicist doing an amplitude interpretation of seismic reflection data. A simple rearrangement of Kirchhoff’s retarded potential equation allows the reflection process to be evaluated as a convolution of the derivative of the source wavelet with a term called the “wavefront sweep velocity”. The wavefront sweep velocity is a measure of the rate at which the incident wavefront covers the reflecting boundary. By comparing wavefront sweep velocities for geologic models with different curvature, one obtains an intuitive feeling for the relation of diffraction and reflection amplitudes to boundary curvature. Also, from this convolutional form of the wave equation, the geometrical optics solution for the reflection amplitude is easily obtained. But more important, from the wavefront sweep velocity approach, a graphical method evolves which allows the geophysicist to use compass and ruler to estimate the effects of curvature and diffractio...

Lithology, color-coded seismic sections; the calibration of AVO crossplotting to rock properties

In the late 1960s, several oil companies noticed that, in environments of young clastic sediments, large seismic amplitudes were associated with gas‐saturated sands. This method of correlating lithology to normal incidence (NI) reflectivities was appropriately named the bright spot technique. However, it quickly became apparent that not all large amplitudes were necessarily associated with gas reservoirs and, much to our chagrin, not all gas reservoirs had large amplitudes. For the next decade, geophysicists tried numerous techniques to resolve the ambiguity associated with lithologic identification by means of the seismic attribute NI. This met with various degrees of success. Finally, Ostrander’s work on amplitude variation with offset (AVO) led to the development of another seismic attribute(s) which improved our discrimination of lithologies (see “Plane‐wave reflection coefficients for gas sands at nonnormal angles of incidence,” Geophysics 1984). But proper application of this new attribute along wit...

Is AVO the seismic signature of lithology? A case history of Ship Shoal-South Addition

Many times we’ve heard, “I’ve tried amplitude‐versus‐offset (AVO) and it doesn’t work in my area.” Before casting AVO aside, let’s look at the process one more time. AVO analysis is actually a two‐step process. The first step relates the seismic response (CDP gather) to the rock’s velocity, density and Poisson’s ratio; the second step relates these rock properties to the lithologies (sand, shale, etc.).

Interpretative lessons from three-dimensional modeling

Three‐dimensional (3-D) seismic modeling has been accomplished by describing geologic surfaces with triangular plates and then computing the seismic response by Kirchhoff wave theory. The resulting time sections illustrate many interesting 3-D phenomena which are useful in interpreting geologic structures. Three‐dimensional resolution studies relate the concept of Fresnel zone reflection to seismic resolution. If high resolution is desired both horizontally and vertically, then not only is a dense field survey required, but also a detailed amplitude study. The dense seismic coverage is required to map the focal line of concave boundary edges, which are difficult to delineate with conventional seismic data. Additional studies on complex models, such as grabens and 3-D permeability traps, associate interpretational pitfalls to a wandering specular reflection path, that is, “side‐swipe.” In each geologic model, maximum resolution is obtained on a principal plane line (dip line). If a seismic dip line is not ...

Multicomponent AVO analysis, Vacuum field, New Mexico

Shear‐wave amplitude variation with offset (AVO) analysis can be used to map changes in density, shear‐wave velocity, and fracturing at reservoir scale by allowing the influence of each factor to be separately extracted from the observed seismic response. Weighted least‐squares inversion of the anisotropic reflection coefficients was implemented to find the shear‐wave splitting coefficient and velocity‐contrast parameters. A time‐lapse nine‐component, 4‐D seismic survey acquired over Vacuum field in Lea County, New Mexico, was used to test our methodology of shear‐wave AVO analysis and to compare the results with well production and azimuthal P‐wave AVO analysis.Weighted least‐squares shear‐wave AVO stacks of the splitting parameter were found to be excellent predictors of well fluid‐production performance, implying a strong link between seismically inferred fracturing and reservoir‐scale permeability of the San Andres dolomites at Vacuum field. Analysis of the shear‐wave velocity contrast indicated the p...

Identification of lithology in the Gulf of Mexico

In a small town outside of Houston, a local rancher was overheard saying, “Do you have any 3-D seismic across your place? You ought to get some, because it tells you exactly what’s down there and where to drill.” Yes, the transfer of technology has been accelerated by new electronic media such as the Internet, but is it possible that it bypassed the geophysicists?

Significance of geopressure in predicting lithology

Maybe this is too late in the exploration program. To emphasize this position, we will argue that “if you don’t post geopressure on your seismic section, then you are only interested in a structural interpretation … not lithology.” To persuade you, the interrelationship of geopressure to sand percentage, rock type, depth, and depositional environment will be shown to correlate strongly to the velocity and density assigned to a particular lithology. Surprisingly, this holds not only for seismic but also for potential fields.

Lithologic color‐coded sections by AVO crossplots

AVO processing and interpretation can yield a lithologic section through a two-step process. First, the well-log curves are analyzed to establish the normal-incidence reflectivity (NI) and the poisson reflectivity (PR). These (NI, PR) pairs are then crossplotted for visual analysis of the grouping of the lithologic boundaries, such as shale over a water-saturated sand or a shale over a gas-saturated sand. The second step uses NI and PR reflectivity sections extracted from seismic data through AVO inversion. The two reflectivity sections are combined into a single color section by assigning each time sample, t, a color based on the spatial position that NI(t) and PR(t) occupy within the crossplot of NI vs PR. The color assignment is based on the separation of the expected lithologic boundaries in the NI vs PR crossplot conducted in the first step. The color on the resulting section then correlates to the lithologic boundaries established in the petrophysical calibration. The entire procedure is performed interactively on a workstation.