Hydrocarbon-saturated Reservoirs Research Articles

Generalized Buckley-Leverett problem

Analysis of the effect produced by thermal and gas treatment on oilfield reservoirs of the Bazhenov formation involves the dynamics of a porous saturated medium with a multiphase multicomponent fluid, taking into account the chemical and physicochemical transformations under thermal and gas injection. This work is a qualitative investigation into such processes based on a simplified partial model allowing analytical study. The process of hot water injection into hydrocarbon-saturated reservoirs is considered. The physical statement of the problem is the generalization of the BuckleyLeverett problem additionally taking into account mass and heat sources. The purpose is to study the mechanism of heat and mass transfer in a porous medium with allowance for chemical and physicochemical transformations. By way of example, an analytical solution of the problem is considered using a specific algebraic expression for the Buckley-Leverett function. Our research makes it possible to identify some qualitative features of the general model and to draw significant practical conclusions. The results can be applied to the investigation into a wide scope of processes of liquid-liquid displacement in a porous medium with two-phase and multicomponent fluid in the presence of heat and mass sources.

A comparison between methods that discriminate fluid content in unconsolidated sandstone reservoirs

Three seismic attributes commonly used to predict pore fluid and lithology are the fluid factor [Formula: see text], Poisson impedance (PI), and lambda-rho [Formula: see text]. We evaluated the pore-fluid sensitivity of these attributes with both well-log and seismic data in Tertiary unconsolidated sediments from the Gulf of Mexico where sand and shale are the only expected lithologies. While the sensitivity of one attribute versus another to discriminate pore fluid is often debated in the literature, the sensitivities of the three attributes are not independent but can be traced back to the fluid factor, which is a function of the P- and S-wave normal-incident reflection coefficients. Interestingly, the fluid factor, which is a reflectivity attribute, at the top of a hydrocarbon-saturated reservoir, is basically independent of the shale properties above the reservoir. It is a function of the brine and hydrocarbon impedances of the reservoir. The next attribute, Poisson impedance, is thenequal to the fluid factor times the sum of the brine and hydrocarbon impedances. Finally, the lambda-rho attribute is equal to the Poisson impedance multiplied by the same impedance sum. Essentially, the same scale factor differentiates these attributes, which does not significantly affect the sensitivity of the attributes. PI is the basis of the sensitivity for these attributes. As a means of testing their sensitivity for predicting pore fluid, we generated the three attributes along with their statistical distributions for different pore fluids for 183 reservoirs. The well-log statistical descriptions were then used to calibrate the seismic amplitude in a 3D survey to reflectivity values, thus allowing pore-fluid classification schemes based on Bayes’ decision rules. In essence, seismic-amplitude quantification was based on regional statistics rather than individual wells within the 3D seismic survey to delineate the portions of the reservoir that were saturated with oil, gas, or brine.

海洋ＣＳＥＭ法による油ガス層分布の把握技術の現状とその可能性

Recently the marine controlled-source electromagnetics (CSEM) is applied commercially to the problem of detecting the presence of hydrocarbon filled layers in the sub-sea formations, and a number of companies are now providing this service.In this paper, we return to fundamentals of electromagnetic (EM) method. Transmission frequencies used in the marine CSEM are typically between 0.01 and 10Hz. As such low frequencies, the behavior of EM field in subsurface is governed by the diffusion equation rather than the wave equation. The EM field radiated by an electric source can be considered to consist of two different modes : a TM mode component and a TE mode component. An analysis of both the TE and TM mode holds the potential to determine if the increase in the measured EM field is caused by the presence of hydrocarbon saturated reservoir or other resistive bodies in the subsurface. The physics of CSEM in shallow water is also examined by using simple 1-D models. This would show that the concept of air interaction, rather than air wave, is appropriate because of complex coupling between signals interacting with seafloor and air.We then apply the inversion analysis to frequency-domain CSEM sounding data acquired in the offshore of Australia, investigate how the marine CSEM could reconstruct resistivity image of gas bearing formation. The survey area comprises two towed lines, covering discovered gas field. The transmitter antenna is a horizontal electric dipole of length about 250m, towing along profiles at an average of 30m above the receivers. For the inversion process, we use a starting model with homogeneous background of 1.0 ohm-m below the sea bottom. No further a priori information is utilized during the inversion. The inversion reaches acceptable data misfit, produced images of the resistive target which can be interpreted gas bearing formation.

Reservoir permeability from seismic attribute analysis

In case of porous fluid-saturated medium the Biot's poroelasticity theory predicts a movement of the pore fluid relative to the skeleton on seismic wave propagation through the medium. This phenomenon opens an opportunity for investigation of the flow properties of the hydrocarbon-saturated reservoirs. It is well known that relative fluid movement becomes negligible at seismic frequencies if porous material is homogeneous and well cemented. In this case the theory predicts an underestimated seismic wave velocity dispersion and attenuation. Based on Biot's theory, Helle et al. (2003) have numerically demonstrated the substantial effects on both velocity and attenuation by heterogeneous permeability and saturation in the rocks. Besides fluid flow effect, the effects of scattering (Gurevich, et al., 1997) play very important role in case of finely layered porous rocks and heterogeneous fluid saturation. We have used both fluid flow and scattering effects to derive a frequency-dependent seismic attribute which is proportional to fluid mobility and applied it for analysis of reservoir permeability.

Asymptotic airwave modeling for marine controlled-source electromagnetic surveying

Marine controlled-source electromagnetic (CSEM) surveying, also called seabed logging, is a technique for finding resistive layers in the subsurface, which can be hydrocarbon-saturated reservoirs. The EM signal from the horizontal electric dipole source induces an airwave along the air/sea surface that interferes with the signal from the subsurface and dominates at larger offsets. The airwave commonly denotes the energy that propagates from the source via the atmosphere to the receiver on the seabed. The airwave component is especially problematic in shallow waters, where it is less attenuated during its up-and-down propagation in the water column than for deeper waters. An asymptotically derived space-domain equation that describes the airwavecomponent in a water half-space bounded by air is well known from the EM literature. We demonstrate that by taking into account the reflections and reverberations of the airwave component in the water column between the seabed and the sea surface at both the source side and the receiver side, this equation can be generalized to a water layer. The new model we present can serve as an integrity check for other modeling schemes. Our airwave model shows how the airwave component depends on water depth, source-receiver range, frequency, and seabed resistivity. The model is verified by extensive numerical testing. Finally, we show how the source-induced airwave may affect the marine CSEM recordings and how the airwave component in principle can be suppressed by a modeling-and-subtraction approach.

AVO attribute analysis and seismic reservoir characterization

This article summarizes some basic concepts in AVO processing and the computation of prestack seismic attributes. Seismic modelling forms the basis for understanding the seismic signature. It helps in the prediction of reservoir characteristics away from well control points. Reliable estimation of petrophysical parameters is needed as input for such studies. These petrophysical estimates are an integral part of more advanced reservoir characterization and modelling. First, the AVO principles are described and various prestack attributes are presented. Subsequently, the elastic approach is discussed and finally the benefits of seismic modelling with advantages of multi-disciplinary reservoir studies are demonstrated. The amplitude character of seismic reflections varies with offset, due to changes in the angle of incidence. The commondepth- point (CDP) gather (Fig. 1a) shows the variation for different traces. Figure 1b illustrates the changes in the seismic response when a water-wet brine-filled reservoir is replaced by oil or gas. The synthetics are calculated along a normal incidence and zero offset trajectory. The hydrocarbon saturation is set at 80% (Robinson et al., 2005). Both hydrocarbon cases show brightening of the reflection with respect to the brinefilled scenario. The sands have lower acoustic impedance (AI) than the encasing shales. Not only the top reservoir reflection shows this increased contrast tendency, but the seismic loop directly below it also manifests considerable changes. Figure 2 illustrates a positive gas-sand reflection decreasing with offset, while the negative water-wet reservoir above shows less reflectivity change. The polarity of the data is normal, i.e. an increase in acoustic impedance with depth (or hard kick) corresponds to a peak to the right on the seismic traces. The two highlighted reservoirs are of differing petrophysical character and the encasing geology (compaction/lithology) changes with depth. Although this kind of amplitude variation is evident on the prestack CMP gathers, it has been somewhat ignored in the past by interpreters because they work primarily with the stacked migration data set. Nowadays, special studies are conducted on a routine basis to analyse the behaviour of the ‘amplitude-versus-offset’ (AVO-studies). This type of data contains detailed information on the porefill of reservoirs (e.g. Ostrander 1984; Castagna and Backus 1993; Chiburis et al., 1993; Hilterman 2001; Veeken et al., 2002; Da Silva et al., 2004a). Ultimately it will lead to a more efficient evacuation of hydrocarbons with substantially improved recovery factors (Fig. 3). The amplitude behaviour of the different raypaths also varies according to the porefill and lithology. Water-filled reservoirs often show variations in amplitude with offset that are different from those of hydrocarbon-filled reservoirs. The change in zero-offset reflectivity R0, or intercept, is the most diagnostic feature. The seismic response depends on the encasing geology, porefill, and interference effects. It varies with depth and differs in various parts of the world. Studying the prestack differences in detail can indicate the causes of near- and far-offset amplitude variability (Fig. 4). The seismic signature from a gas sand is different from the brine-filled response when the same reservoir is observed under similar conditions. In such a situation, the encasing geology is probably the same and has little influence on the observed anomalous amplitude behaviour. A distinct change in zero-offset reflectivity is probably the most remarkable phenomenon. Changes in amplitude with offset can occur in hydrocarbon- as well as water-bearing reservoirs; in that case the intercept might contain the vital porefill information. The AVO effect represents a potentially powerful tool to discriminate between water- and hydrocarbon-saturated reservoirs. However, it means going back to the prestack domain. It should be ensured that the data on individual CDP gathers come from a consistent subsurface location. This is generally achieved by a proper migration of the input data set (prestack time migration, Da Silva et al., 2004b). Careful data preconditioning is essential when quantitative interpretation is the ultimate aim (Veeken and Da Silva, 2004).