Bill Goodway

Improved AVO Fluid Detection And Lithology Discrimination Using Lamé Petrophysical Parameters; “λρ”, μρ, λμ Fluid Stack”, From P And S Inversions.

However the underlying physics in the wave equation; does not involve seismic velocities, but instead the ratio of density (p) to modulus (M). So converting velocity measurements to Lame’s modulii parameters of rigidity and incompressibility (h) offers new insight into the original governing rock property factor It will be shown that an improved identification of reservoir zones is possible by the enhanced sensitivity to pore fluids from pure compressibility, as well as lithologic variations represented by fundamental changes in rigidity, incompressibility, and density parameters as opposed to mixed parameters of seismic velocities. Theory, method and log analysis motivation Standard analysis methods given above, though appearing different, rely fundamentally on Vp, Vs and density variations, thereby masking the original modulus parameterization as mentioned. Some authors point out the need for a more physical insight afforded by rigidity (Wright 1984,Thomsen 1990,Castagna et al. 1993b) in the above equations. Castagna also indicates that the link between velocity and rock properties for pore fluid detection, is through the bulk modulus that is embedded in Vp. However both and more so Vp have the most sensitive pore fluid indicator diluted by varying factors of the rock matrix indicator (ie. non-pore fluid). This can be seen in the following relationships; and Recent AVO inversion schemes incorporate an explicit density term (Stewart 1995, Smith 1996) to potentially extract modulii, but as the number of unknowns increase and exceed the measured quantities (intercept and offset gradient amplitude) so these complex equations are less robust and the extracted values more inaccurate. From these observations the standard approaches may be considered either too insensitive or unnecessarily complex as rock property indicators. The proposal here is to use modulii/density relationships to velocities V or impedances I, given as; + and These relationships enable extraction of the orthogonal Lame parameters and from logs with measured density or and from seismic without known density. The simple derivations are; and = 2 = Note, Poisson’s ratio analysis being related to (Vp/Vs) 2 , comes closes to measuring the most “rock property sensitive”

Seismic petrophysics and isotropic-anisotropic AVO methods for unconventional gas exploration

Exploration and drilling for natural gas in North America has moved radically away from conventional reservoirs to focus on unconventional reservoirs such as tight gas sands and shales. These reservoirs have low porosity and near-zero permeability with gas stored in natural fractures and within the matrix porosity. Economic gas production requires hydraulic fracture stimulation to open connections to existing natural fractures or matrix porosity, and successful stimulation depends on the formations geomechanical brittleness being capable of supporting extensive induced fractures. However, despite adequate stimulation, significant variations exist between wells in expected ultimate recovery (EUR) due to the heterogeneity of these resource plays. Consequently, predicting natural fractures or fracture-prone “sweet spots” is essential to optimize development of such plays.

Estimation and interpretation of P and S impedance volumes from simultaneous inversion of P-wave offset seismic data

Summary Seismic amplitude variation with offset holds information on density and two elastic parameters: compressional and shear velocities (or impedances). We simultaneously invert multiple offset stacks to transform P-wave offset seismic reflection data to these parameters. Prior to the inversion, wavelets are estimated separately for each offset stack. This enables the inversion to compensate for offset-dependent phase, bandwidth and tuning and nmo stretch effects. The impedance volumes can be interpreted separately or combined to estimate other geophysical parameters which might optimally discriminate between facies. In this regard, we have found the Lame’ parameters, Lambda and Mu particularly useful. From well log analysis we expect that reservoir sands have lower Lambda (incompressibility) and higher

Integrating Geophysics, Geology and Petrophysics: A 3D seismic AVO and borehole/logging case study

Introduction Upper Mannville aged strata in southern Alberta consist of a complex lithologic assemblage of narrow shoestring like “Glauconite” and “Lithic” valley-systems trending roughly north-south and variably cutting down into older regional Glauconite, Ostracod and Basal Quartz strata. These valley systems are commonly filled with hydrocarbon-bearing sandstones with varying reservoir quality. In the study area, the Glauconite valley systems are up to 35 meters deep, 2 kilometres wide and several tens of kilometres long. The younger “Lithic” valleysystems generally follow the same trend as the Glauconite valleys and are up to 40 meters deep, 3 to 4 kilometres wide and also several tens of kilometres long. In 1996, a 3D seismic survey was acquired over the valley trends to image reservoir quality sands. It is often difficult to seismically distinguish between Glauconite sand and Ostracod shale by using poststack amplitudes. Improved techniques from recent prestack seismic work suggest that AVO (Amplitude Versus Offset) might be an effective way to extract rock properties and detect gas (Smith and Gidlow, 1987; Gidlow et al., 1992; Fatti et al., 1994, Goodway et al., 1997). Smith and Gidlow (1987), Gidlow et al(1992) and Fatti et al. (1994) proposed a method to create a display which highlights the Vp/Vs ratio anomaly (often caused by the presence of gas) by using the so called “fluid factor stack”. Goodway et al. (1997) proposed a new improved fluid detection and lithology discrimination indicator using petrophysical parameters and where and are Lame’s constants (incompressibility and rigidity) and is density. The geological and geophysical effort in this area is to determine where the two valleys are present, and to differentiate sands from shale. Geology and Reservoir Quality Log analysis and core data, where available, indicate that the Glauconite sandstones generally have good to excellent reservoir quality whereas the Lithic sandstones are generally moderate to poor quality rocks. For example, the Glauconite sandstones in well B (Figures 1 & 2) have core porosities ranging from 18 to 26% and permeabilities ranging from 948 to 4900 md.. In contrast, the Lithic sandstones in well C (Figure 1) have core porosities ranging from 10 to 14% and permeabilities from 1 to 40 md.. Glauconite channels in the study area produce both oil and gas whereas Lithic channels produce primarily gas. The differences in reservoir quality between the Glauconite and Lithic channels are related to major differences in sandstone framework grain composition. Sedimentological interpretations from available core indicate that the Glauconite and Lithic channels consist predominantly of fine to medium grained fluvial sandstone at the base and grade upwards into finer grained marine influenced (estuarine) deposits at the top. Typical regional, non-channel, deposits in this area can be seen in wells A & D in Figure 1. The Ostracod interval, which consists of shale and limestone is a significant regionally extensive stratigraphic marker. Absence of the Ostracod is one of the key correlation indicators for downwards incision by overlying Glauc and Lithic channels. Petrophysical Analysis and Lame Parameters Petrophysical parameters for “complex” lithology, porosity, and fluid saturations were modeled. A rather complete log-data set including density, neutron, sonic, gamma ray and magnetic resonance logs permitted a comprehensive model to be developed and correlated to core lithology, porosity and saturation data. This “complex” lithology model is required to account for bitumen, gas, irreducible water and intraparticle porosity evident in the log, core and thin section data. Magnetic resonance data enables meaningful evaluation of bitumen and irreducible water in this lithology. Model parameter selection is constrained by comparison of model results to core lithology, porosity and fluid saturations. The petrophysical model illustrated by figure 2 for well B shows a clean quartz rich sand lithology having a maximum effective porosity of 0.26 (core porosity overlaid in red). The porosity match deviates in intervals where intraparticle porosity is not included in the core porosity. Effective porosity is reduced by shaliness at the top and by bitumen at the base of the sand. Modeled hydrocarbon saturation is overlain by core oil saturation (in red). The saturation curves correspond in intervals containing residual oil and deviate in gas bearing intervals.

Developing Templates For Integrating Quantitative Geophysics And Hydraulic Fracture Completions Data: Part I - Principles And Theory

Summary Unconventional resource plays require that geophysicists redefine the value seismic brings for economic development of these assets. A large part of developing resource plays comes from optimizing engineering practices. Understanding that seismic data contains information regarding resource potential, rock properties, in-situ stress, reservoir pressure and fracture intensity/orientation allows for educated and optimized large scale development plans. The heuristic interpretation templates provided herein outline a method to interpret seismic data for estimated ultimate recovery (EUR) and the important physical properties for hydraulic fracturing all of which provide insight for optimizing completion efforts.

AVO analysis to extract rock parameters on the Blackfoot 3C-3D seismic data

Summary The Blackfoot field, southeast of Calgary, has produced oil and gas from a Glauconitic compound incised-valley system. The Glauconitic compound incised-valley has three different cycles of incision and valley fill: Upper, Lithic, and Lower incisedvalleys. The Upper and Lower incised-valleys are the main reservoirs. The geophysical interpretation of compressional PPseismic data resulted in the definition of the Glauconitic incised-valley width extent, and in the mapping of the Upper and Low er incised-valleys. However, the nature of the fill within the incised-valleys remains unknown. In an effort to discriminate litho logy and to detect fluid, an AVO analysis of the PP-data was run. The products of the rock parameters, incompressibility and rigidity, with density were extracted from the result of seismic inversion, for P and S ‐impedances.

Predicting the statistical properties of the fluid stack

The signal to noise ratio effects the apparent mudrock trend when cross-plotting AVO reflectivity sections such as the P and S impedance reflectivity sections. The effect of noise can be predicted using the covariance matrix and traditional error analysis methodologies. The slope of the data in cross-plot space is influenced by both the geologic trend defined by the mudrock relationship and the error in estimating the reflectivity series. For signal to noise ratios greater than one, this second influence is relatively minor. The fluid stack provides statistically independent information about the fluid and rock properties in a robust fashion.

Introduction to this special section: Mining geophysics

It has been almost exactly four years since the last TLE special section on mining was published and at that time the OECD was on the brink of the worldwide “great recession” brought on by the collapse of the U.S. housing market and consequent bank insolvency such as the Lehmans bankruptcy in September of that year. Just prior to this event, energy, metals, and food commodities had spiked to their highest relative price since the late 1970s (Figure 1).

Recent Advances In Application of AVO In Carbonate Reservoirs: Calibration And Interpretation

Summary The application of amplitude versus offset (AVO) in the analysis of carbonate reservoirs is on the increase in the Western Canadian Sedimentary Basin (WCSB). This has contributed to a rapidly increasing knowledge of the physical properties of carbonate rocks, and in the active exploration and delineation of carbonate reservoirs. It has been found that not only porosity but also fluid effects may be determined through AVO. Information from a carbonate reservoir, especially that of a fluid effect can be obtained from basic AVO gather and attribute analysis as well as elastic parameter inversion. Recent advances in these areas are reviewed. Furthermore this paper includes new studies in carbonate rock properties, carbonate AVO characteristics due to fluid effects, and elastic rock properties that form the basis for calibration and interpretation, as key issues to be considered.

3-D AVO and migration

The effects of different migrations on AVO are tested using a relatively unstructured data set. In these data, the differences between the migrated and unmigrated data are minimal because the migration does not move data very far. Therefore, any significant differences in AVO must be primarily due to the amplitude preserving effects of the migration. Results are compared to AVO derived from NMO only gathers, which have good correlation to well control.