Simultaneous Impedance Inversion Research Articles

Reservoir characterization over the Lille Prinsen and Ivar Aasen fields in the Norwegian North Sea using ocean-bottom-node seismic data — A case study

We have developed an integrated workflow for estimating elastic parameters within the Late Triassic Skagerrak Formation, the Middle Jurassic Sleipner and Hugin Formations, the Paleocene Heimdal Formation, and the Eocene Grid Formation in the Utsira High area of the Norwegian North Sea. Our workflow begins with petrophysical analysis carried out at the available wells. Then, model-based prestack simultaneous impedance inversion outputs were derived, and attempts were made to estimate the petrophysical parameters (the volume of shale, porosity, and water saturation) from seismic data using extended elastic impedance. On not obtaining convincing results, we switched over to multiattribute regression analysis for estimating them, which yielded encouraging results. Finally, the Bayesian classification approach was used for defining different facies in the intervals of interest.

Seismic reservoir characterization of the Bone Spring and Wolfcamp Formations in the Delaware Basin: Challenges and uncertainty in characterization using rock physics — A case study: Part 2

The discrimination of fluid content and lithology in a reservoir is important because it has a bearing on reservoir development and its management. Among other things, rock-physics analysis is usually carried out to distinguish between the lithology and fluid components of a reservoir by way of estimating the volume of clay, water saturation, and porosity using seismic data. Although these rock-physics parameters are easy to compute for conventional plays, there are many uncertainties in their estimation for unconventional plays, especially where multiple zones need to be characterized simultaneously. We have evaluated such uncertainties with reference to a data set from the Delaware Basin where the Bone Spring, Wolfcamp, Barnett, and Mississippian Formations are the prospective zones. Attempts at seismic reservoir characterization of these formations have been developed in Part 1 of this paper, where the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, accounting for the temporal and lateral variation in the seismic wavelets, and building of robust low-frequency model for prestack simultaneous impedance inversion were determined. We determine the challenges and the uncertainty in the characterization of the Bone Spring, Wolfcamp, Barnett, and Mississippian sections and explain how we overcame those. In the light of these uncertainties, we decide that any deterministic approach for characterization of the target formations of interest may not be appropriate and we build a case for adopting a robust statistical approach. Making use of neutron porosity and density porosity well-log data in the formations of interest, we determine how the type of shale, volume of shale, effective porosity, and lithoclassification can be carried out. Using the available log data, multimineral analysis was also carried out using a nonlinear optimization approach, which lent support to our facies classification. We then extend this exercise to derived seismic attributes for determination of the lithofacies volumes and their probabilities, together with their correlations with the facies information derived from mud log data.

A robust workflow for performing joint impedance inversion and its applications

Multicomponent seismic data offer several advantages for characterizing reservoirs with the use of the vertical component (PP) and mode-converted (PS) data. Joint impedance inversion inverts both of these data sets simultaneously; hence, it is considered superior to simultaneous impedance inversion. However, the success of joint impedance inversion depends on how accurately the PS data are mapped on the PP time domain. Normally, this is attempted by performing well-to-seismic ties for PP and PS data sets and matching different horizons picked on PP and PS data. Although it seems to be a straightforward approach, there are a few issues associated with it. One of them is the lower resolution of the PS data compared with the PP data that presents difficulties in the correlation of the equivalent reflection events on both the data sets. Even after a few consistent horizons get tracked, the horizon matching process introduces some artifacts on the PS data when mapped into PP time. We have evaluated such challenges using a data set from the Western Canadian Sedimentary Basin and then develop a novel workflow for addressing them. The importance of our workflow was determined by comparing data examples generated with and without its adoption.

Seismic reservoir characterization of Utica-Point Pleasant shale with efforts at fracability evaluation — Part 2: A case study

The Utica Formation in eastern Ohio possesses all the prerequisites for being a successful unconventional play. Attempts at seismic reservoir characterization of the Utica Formation have been discussed in part 1, in which, after providing the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, and building of robust low-frequency models for prestack simultaneous impedance inversion were explained. All these efforts were aimed at identification of sweet spots in the Utica Formation in terms of organic richness as well as brittleness. We elaborate on some aspects of that exercise, such as the challenges we faced in the determination of the total organic carbon (TOC) volume and computation of brittleness indices based on mineralogical and geomechanical considerations. The prediction of TOC in the Utica play using a methodology, in which limited seismic as well as well-log data are available, is demonstrated first. Thereafter, knowing the nonexistence of the universally accepted indicator of brittleness, mechanical along with mineralogical attempts to extract the brittleness information for the Utica play are discussed. Although an attempt is made to determine brittleness from mechanical rock-physics parameters (Young’s modulus and Poisson’s ratio) derived from seismic data, the available X-ray diffraction data and regional petrophysical modeling make it possible to determine the brittleness index based on mineralogical data and thereafter be derived from seismic data.

Seismic-scale petrophysical interpretation and gas-volume estimation from simultaneous impedance inversion

Simultaneous impedance inversion was performed to obtain the seismic-scale P- and S-wave impedances as well as the bulk density volumes from seismic angle stacks at a siliciclastic turbidite offshore gas reservoir. To translate these variables into seismic-scale total porosity (φ), clay content, and water saturation (Sw), we used a deterministic rock-physics model established at the well. A crucial input into this model is the bulk modulus (Kf) of the brine/gas system. We need to link it to Sw at the seismic scale. This link can be one of simple mixing laws, such as harmonic and arithmetic. Alternately, it can be derived at the well by using upscaled variables and ensuring that they obey the well-data-driven rock-physics model. These different Kf-Sw relations produce different interpretations for φ and Sw thus allowing one to assess the variability in the estimates of the gas volume in place that is proportional to the product of φ and (1 − Sw).

Characterization of shallow high-amplitude seismic anomalies in the Hoop Fault Complex, Barents Sea

The shallow migrating hydrocarbon fluids in the western Barents Sea are usually found to be associated with high seismic amplitudes. We have attempted to characterize such shallow high-amplitude anomalies in the Hoop Fault Complex area of the western Barents Sea. The workflow is devised for discrimination of anomalies that are associated with the presence of hydrocarbons from those that are not, and quantifying them further includes the computation of a set of seismic attributes and their analyses. These attributes comprise coherence, spectral decomposition, prestack simultaneous impedance inversion, and extended elastic impedance attributes, followed by their analysis in an appropriate crossplot space, as well as with the use of rock-physics templates. Finally, we briefly evaluate the futuristic efforts being devoted toward the integration of diverse data types such as P-cable seismic as well as controlled-source electromagnetic data so as to come up with an integrated assessment for the prospects and to mitigate risk.

Simultaneous impedance inversion and interpretation for an offshore turbiditic reservoir

By using simultaneous impedance inversion, we obtained P- and S-wave impedance ([Formula: see text] and [Formula: see text]) volumes from angle stacks at a siliciclastic turbidite oil reservoir offshore northwest Australia. The ultimate goal was to interpret these elastic variables for fluid, porosity, and mineralogy. This is why an essential part of our workflow was finding the appropriate rock-physics model based on well data. The model-corrected S-wave velocity [Formula: see text] in the wells was used as an input to impedance inversion. The inversion parameters were optimized in small vertical sections around two wells to obtain the best possible match between the seismic impedances and the upscaled impedances measured at the wells. Special attention was paid to the seismically derived [Formula: see text] ratio because we relied on this parameter for hydrocarbon identification. Even after performing crosscorrelation between the angle stacks to correct for two-way traveltime shifts to align the stacks, these stacks did not indicate a coherent amplitude variation with angle (AVA) dependence. To deal with this common problem, we corrected the mid and far stacks by using the near and ultrafar stacks as anchoring points for fitting a [Formula: see text] AVA curve. This choice allowed us to match the seismically derived [Formula: see text] ratio with that predicted by the rock-physics model in the reservoir. Finally, the rock-physics model was used to interpret these [Formula: see text] and [Formula: see text] for the fluid, porosity, and mineralogy. The new paradigm in our inversion/interpretation workflow is that the ultimate quality control of the inversion is in an accurate deterministic match between the seismically derived petrophysical variables and the corresponding upscaled depth curves at the wells. Our interpretation is very sensitive to the inversion results, especially the [Formula: see text] ratio. Despite this fact, we were able to obtain accurate estimates of porosity and clay content in the reservoir and around it.

Porosity, mineralogy, and pore fluid from simultaneous impedance inversion

We find that in a quartz/clay system, P- and S-wave impedances (IP and IS, respectively) each uniquely depend on a different linear combination of the total porosity and clay content. This implies that if the pore fluid is known, we can resolve these two seismically derived impedances for porosity and clay content. Key to such interpretation is rock-physics diagnostics that provide a theoretical rock-physics model to quantitatively explain well data by relating IP and IS to porosity, clay content, and pore fluid. The well data conditioned according to this model serve as input to simultaneous impedance inversion. Poisson's or the IP/IS ratio serves as the pore-fluid identifier. We give an example of such rock-physics-based interpretation of seismically derived impedances for rock properties based on well and seismic data from an offshore oil field.

The effects of seismic data conditioning on prestack simultaneous impedance inversion

It is well known among the seismic data processing community that the demands of reservoir characterization are far more rigorous than those of structural interpretation. Further, the undesired prestack seismic phenomena that need to be diminished or removed prior to reservoir characterization are also well known. The objective of this paper is to quantify the advantages of performing prestack data conditioning prior to reservoir characterization. Three specific seismic properties that will be addressed are: (1) signal-to-noise ratio (SNR), (2) offset-dependent frequency loss, and (3) gather alignment.

The use of seismic attenuation to aid simultaneous impedance inversion in geophysical reservoir characterization

The current state-of-the-art in reservoir characterization is to input properly conditioned gathers into a prestack simultaneous impedance inversion workflow. Simultaneous inversion is defined as the simultaneous solution of all unknown quantities in a reflectivity equation. If two-term inversion is run, then the outputs are P-impedance (AI) and S-impedance (SI). These two quantities are then crossplotted and pay zones delineated using polygons created from a similar crossplot of upscaled AI and SI well logs.