Introduction

There are several possible objectives in performing well ties:

• zero phasing: checking whether data are zero phase, and helping to adjust the phase if required,

• horizon identification: relating stratigraphic markers in the well to loops on the seismic section,

• wavelet extraction for seismic inversion or modelling,

• offset scaling: checking whether the seismic data have been ‘true amplitude’ processed to have the correct AVO behaviour, and adjusting amplitudes if necessary.

Achieving these objectives requires integration of regional interpretation experience with well tie analysis, linking surface seismic to synthetic seismograms and vertical seismic profiles (VSPs), as shown in Fig. 4.1. One way of looking at the well tie is that it is the interpreter's chance to conduct an experiment to test the connection between the geology and the seismic data. In practice, there are numerous issues to consider and an analytical approach is useful. There are some situations where the tie and the phase of the seismic data are not in doubt; in other cases there is significant uncertainty. Estimates of well tie and wavelet accuracy frame the context for assessing the quality of calibration in an interpretation and amongst other benefits they provide insight into the feasibility of a good quality trace inversion (Chapter 9).

Introduction

Seismic reflections depend on the contrast of the P- and S-wave velocity and density between strata in the subsurface, while the velocity and density depend on the lithology, porosity, rock texture, pore fluid, and stress. These two links, one between the rock’s structure and its elasticity and the other between the elasticity and signal propagation, form the physical foundation of the seismic-based interpretation of rock properties and conditions. One approach to interpreting seismic data for the physical state of rock is forward modeling. Lithology, porosity, stress, pore pressure, and the fluid in the rock, as well as the reservoir geometry, are varied, the corresponding elastic properties are calculated, and then synthetic seismic traces are generated.

These synthetic traces are compared to real seismic data: full gathers; full stacks; and/or angle stacks. The underlying supposition of such interpretation is that if the seismic response is similar, the properties and conditions in the subsurface that give rise to this response are similar as well. Systematically conducted perturbational forward modeling helps create a catalogue (field guide) of seismic signatures of lithology, porosity, and fluid away from well control and, by so doing, sets realistic expectations for hydrocarbon detection and monitoring and optimizes the selection of seismic attributes in an anticipated depositional setting.

Introduction

A decision to drill an amplitude-based prospect must be based on rigorous validation of the seismic anomaly and evaluation of the prospect risk and the potential hydrocarbon volumes. Sometimes there is strong seismic evidence that hydrocarbons are present. Even in this case, careful DHI interpretation and risking of amplitude-supported prospects can reduce the exploration uncertainty and risk and, hence, encourage drilling a wildcat well.

Direct hydrocarbon indicator (DHI) interpretation consists of two phases: (a) recognition of seismic anomalies and (b) validation of the selected anomalies. The validation requires quantitative calibration of rock properties to seismic data (Chapter 11). Prospects with seismic data that contain clear apparent anomalies, possibly indicating a hydrocarbon presence, still have to undergo careful rock-physics-based examination to ensure that these anomalies are not false indicators.

Prospects without obvious amplitude anomalies are also studied using the same worklow to estimate the seismic response from prospective hydrocarbon-bearing reservoirs. If such investigation suggests that DHIs are expected, this exploration opportunity is highly risked and seismic acquisition and processing have to be revisited. On the other hand, if the study suggests that no obvious hydrocarbon indicators are expected, the possibility of hydrocarbon-bearing rocks in this particular prospect cannot be excluded. Such methodologies have been successfully applied to quantifying the exploration risk in many amplitude-supported prospects (Roden et al., 2005; Fahmy, 2006; Forrest et al., 2010; De Jager, 2012; Roden et al., 2012).

Examples of shapes encountered in clastic sequences

The seismic amplitude depends not only on the contrasts of the elastic properties but also on the shape of the elastic property distribution in the subsurface which, in turn, is associated with the underlying rock properties, including the porosity and clay content. In Figure 8.1 we show well data from an offshore oil well that encountered a low-GR hydrocarbon reservoir. The shape on the GR curve is blocky at the bottom but has a gradual low- to high-GR at the top. The porosity and density curves mimic this fining-upwards shape and so does the P-wave impedance. As a result, the impedance contrast at the bottom of the oil-filled interval is larger than at its top and, hence, the amplitude at the bottom is stronger.

It exhibits an AVO response with the normal-incidence positive amplitude becoming increasingly positive with the increasing offset. The reason for this behavior is the positive contrast of the P-wave impedance as well as Poisson’s ratio between the sand and underlying shale (Figure 8.1, top). The character of this reflection would be very different if the sand was wet (Figure 8.1, bottom) as the strong impedance and Poisson’s ratio contrasts present in situ virtually disappear. This is the case where a bright spot, especially at far angle incidence, points to a hydrocarbon-filled interval.

Preface

Rock physics is the part of geophysics concerned with establishing relations between various properties of rocks. Because the elastic radiation is the main agent that allows us to illuminate the subsurface, the primary emphasis of rock physics has been to relate the elastic properties of rock, including the P- and S-wave velocity, P- and S-wave impedance, and Poisson’s ratio to porosity, lithology, and pore fluid. A significant number of such rock physics models (transforms) have been developed based on experimental data or physical theories or both. These models enable us to forward model the elastic properties of rock as a function of porosity, rock texture (arrangement of grains or cavities at the pore-scale level), mineralogy, and the compressibility of the pore fluid. Because the seismic reflection depends on the contrast of the elastic properties in the subsurface, rock physics helps generate synthetic seismic reflections at an interface between two different rock types, such as a non-reservoir rock cap and petroleum reservoir, as well as at a fluid contact within a reservoir itself (e.g., gas/oil contact and oil/water contact).

However, in field applications, we face an inverse problem whose solution is not unique: how to interpret a seismic event, which is manifested by a reflection amplitude that stands out of the background, in terms of reservoir properties and conditions. The inherent difficulty of this problem is that the number of variables required to produce the elastic properties of porous rock is larger than the number of seismic observables. Various approaches have been developed to tackle this uncertainty; most of them based on statistical techniques that help assess the probability of the occurrence of a certain object (e.g., high-porosity sand filled with oil) at a given location in a 3D subsurface. Even when using statistical techniques, forward modeling of seismic reflections based on either well log data or theoretical rock physics is a key element of interpreting seismic data.

Background

Gas hydrates are solids where gas molecules are locked inside cage-like structures of hydrogen-bonded water molecules. The physical properties of hydrates are remarkably close to those of pure ice. According to Helgerud (2001), the P- and S-wave velocity in methane hydrate may reach 3.60 and 1.90 km/s, respectively, while its density is 0.910 g/cm3. The corresponding values for ice are 3.89 and 1.97 km/s, and 0.917 g/cm3, respectively. As a result, sediment with hydrate in the pore space, similar to frozen earth, is much more rigid than sediment filled solely by water.

However, unlike ice, methane hydrate can be ignited. A unit volume of hydrate releases about 160 unit volumes of methane (under normal conditions). Also, unlike ice, hydrate can exist at temperatures above 0° C, but not at room conditions – it requires high pore pressure to form and remain stable.

Such stability conditions are abundant on the deep shelf: high pressure is supported by the thick water column, while the temperature remains fairly low (but above 0° C) at depths of several hundred feet below the sealoor because temperature increase with depth starts at a low level, just a few degrees Celsius at the bottom of the ocean. Hydrates also exist onshore below the permafrost which acts to lower temperature at a depth where the hydrostatic pressure is already high. Favorable pressure and temperature are necessary but not suficient for hydrate generation; its molecular components, water and gas, also have to be available at the same place and time.