Jyoti Behura

Heavy oils: Their shear story

Heavy oils are important unconventional hydrocarbon resources with huge reserves and are usually exploited through thermal recovery processes. These thermal recovery processes can be monitored using seismic techniques. Shear-wave properties,inparticular,areexpectedtobemostsensitivetothechanges in the heavy-oil reservoir because heavy oils change from being solid-like at low temperatures to fluid-like at higher temperatures. To understand their behavior, we measure the complex shearmodulusandthusalsotheattenuationofaheavy-oil-saturated rock and the oil extracted from it within the seismic frequency band in the laboratory. The modulus and quality factor Qoftheheavy-oil-saturatedrockshowamoderatedependence on frequency, but are strongly influenced by temperature. The shear-wave velocity dispersion in these rocks is significant at steam-flooding temperatures as the oil inside the reservoir loses viscosity.Atroomtemperatures,theextractedheavyoilsupports a shear wave, but with increasing temperature, its shear modulus decreases rapidly, which translates to a rapid drop in the shear modulus of the heavy-oil-saturated rock as well.At these low to intermediate temperatures 30°C‐100°C, an attenuation peak corresponding to the viscous relaxation of the heavy oil is encountered also resulting in significant shear-wave velocity dispersion, well described by the Cole-Cole model. Thus, shearwaveattenuationinheavy-oilrockscanbesignificantlylargeand iscausedbyboththemeltingandviscousrelaxationoftheheavy oil. At yet higher temperatures, the lighter components of the heavy oil are lost, making the oil stiffer and less attenuative.The dramaticchangesinshearvelocitiesandattenuationinheavyoils should be clearly visible in multicomponent seismic data, and suggestthatthesemeasurementscanbequalitativelyandquantitatively used in seismic monitoring of thermal recovery processes.

Fluid substitution in rocks saturated with viscoelastic fluids

Heavyoilshavehighdensitiesandextremelyhighviscosities, and they exhibit viscoelastic behavior. Traditional rock physics based on Gassmann theory does not apply to materials saturated with viscoelastic fluids. We use an effective-medium approach known as coherent potential approximation CPA as an alternativefluid-substitutionschemeforrockssaturatedwithviscoelasticfluids.Suchrocksaremodeledassolidswithellipticalfluidinclusions when fluid concentration is small and as suspensions of solid particles in the fluid when the solid concentration is small. Thisapproachisconsistentwithconceptsofpercolationandcritical porosity, and it allows one to model sandstones and unconsolidated sands.We model the viscoelastic properties of a heavyoil-saturated rock sample using CPAand a measured frequencydependent complex shear modulus of the heavy oil. Comparison of modeled results with measured properties of the heavy-oil rock reveals a large discrepancy over a range of frequencies and temperatures. We modify the CPAscheme to account for the effect of binary pore structure by introducing a compliant porosity term. This dramatically improves the predictions. The predicted values of the effective shear modulus of the rock are in good agreement with laboratory data for the range of frequencies and temperatures. This confirms that our scheme realistically estimates the frequency- and temperature-dependent properties of heavy-oil rocks and can be used as an approximate fluid-substitutionapproachforrockssaturatedwithviscoelasticfluids.

Density extraction from P-wave AVO inversion: Tuscaloosa Trend example

Density extraction from amplitude-variation-with-offset (AVO) inversion is thought to be unstable and difficult. Recent research has, however, shown that it is possible to reliably extract density from P-wave reflection data if the interface has significant contrast.

Small-angle AVO response of PS-waves in tilted transversely isotropic media

Field records for small source-receiver offsets often contain intensive converted PS-waves that may be caused by the influence of anisotropy on either side of the reflector. Here, we study the small-angle reflection coefficients of the split converted PS1and PS2-waves RPS1 and RPS2 for a horizontal interface separating two transversely isotropic TI media with arbitrary orientationsofthesymmetryaxis.

An automated cross‐correlation based event detection technique and its application to a surface passive data set

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

Shear Properties of Oil Shales

Organic-rich shales house large untapped amounts of hydrocarbons. In-situ recovery of these hydrocarbons involves thermal cracking and steamflooding of these reservoirs which changes its physical properties, and shear properties in particular. We measure, within the seismic band, the complex shear modulus (and thus also the attenuation) of two oil shale samples, one rich in organic content and the other low in organic content.

The shear properties of oil shales

A vast unexploited source of hydrocarbons is oil shales; i.e., shales rich in kerogen. The Schlumberger Oilfield Glossary defines kerogen as “the naturally occurring, solid, insoluble organic matter that occurs in source rocks and can yield oil upon heating.” The original organic constituents of kerogen are algae and woody plant material. Kerogens have a high molecular weight relative to bitumen or soluble organic matter. Bitumen forms from kerogen during petroleum generation. Estimates vary as to how much oil is contained in oil shale reserves. The United States Office of Naval Petroleum and Oil Shale Reserves estimates some 1.6 trillion barrels of oil are contained in oil shales around the world, with 60–70% of reserves (1.0–1.2 trillion barrels) in the United States. Most U.S. oil shale is concentrated in the Green River Formation in Wyoming, Utah, and Colorado (covering 16,000 square miles).

Autofocusing for Retrieving the Green's Function in the Presence of a Free Surface

Recent work on autofocusing with the Marchenko equation has shown how the Greens function for a virtual source in the subsurface can be obtained from reflection data. The response to the virtual source is the Greens function from the location of the virtual source to the surface. The Greens function is retrieved using only the reflection response of the medium and an estimate of the first arrival at the surface from the virtual source. Current techniques, however, only include primaries and internal multiples. Therefore, all surface-related multiples must be removed from the reflection response prior to the Greens function retrieval. Here, we present a new scheme that includes primaries, internal multiples, and free-surface multiples. In other words, we retrieve the Greens function in the presence of the free surface. The information needed for the retrieval are the reflection response at the acquisition surface and an estimate of the first arrival at the surface from the virtual source. The reflection response, in this case, includes the free-surface multiples; this makes it possible to include these multiples in the imaging operator and it obviates the need for surface-related multiple elimination.

Virtual real source

Estimation of the seismic source signature is an important problem in reflection seismology. Existing methods of source signature estimation (statistical methods and well-log-based methods) suffer from several drawbacks. For example, assumptions of whiteness of the earth response, stationarity of the data, and the phase characteristics of the wavelet have no real theoretical justification and the extracted wavelets may not be reliable. Here, I introduce a method of extracting the source signature based on the theory of seismic interferometry, also known as the virtual source method. Interferometry can be used to extract the scaled impulse response between two receivers. This is the Green’s function scaled by the power spectrum of the source wavelet. If a source location coincides with one of the receiver locations (not necessarily a zero-offset receiver), the recording at the other receiver would be the Green’s function convolved with the source signature. The scaled impulse response, thus differs from the real recording by having an extra source term convolved with it. Deconvolving the real recording with the scaled impulse response gives the source signature, and so this method is named as “Virtual Real Source”. Through modeling examples, I show that the Virtual Real Source method produces accurate source signatures even for complicated subsurface and source signatures. The quality of the extracted wavelet can be improved by using particular time windows and stacking wavelets extracted from different time windows. Source variability within a seismic survey does not pose any problems because interferometry averages the source signatures and the individual source signatures can be extracted reliably using this method. Source signature of each shot can be extracted reliably if they all have similar amplitude spectra even though their phase spectra might be completely different. This method of source signature estimation not only gives accurate traveltimes and amplitudes of reflection events, but also has the potential to solve other issues, such as finding source radiation patterns, measuring intrinsic attenuation, and estimating statics.

Small‐angle AVO response of PS‐waves in tilted TI media

Field records for small source-receiver offsets often contain intensive reflected PS-waves, which are difficult to model without introducing velocity anisotropy on either side of the reflector. Here, we study the small-angle reflection coefficients of the split converted PS1and PS2-waves (RPS1 and RPS2) for a horizontal interface separating two transversely isotropic media with arbitrary orientations of the symmetry axis.