Elastic Property Modeling, Extended Elastic Impedance (EEI) and Curve-Pseudo Elastic Impedance (CPEI) Inversion for Pore Type Analysis and Hydrocarbon Distribution in Carbonate Reservoir, Kujung I Formation, “Humaira” Field, North East Java Basin

The complexity of the pore shape in carbonate rocks causes the need for a special strategy to characterize carbonate reservoir. The more information used, the more accurate the reservoir characterization will be. Pore type analysis is the important study because it relates to the fluid flow properties. The elastic property modeling show a good match to the actual data. The results of the well log and petrophysical data analysis show that the gas zone is located at the upper side of Kujung I Formation. Based on rock physics modeling result, the possible pore type developing in the Kujung I Formation is reference pore with the dominance of the aspect ratio value of about 0.17-0.19. The carbonate layer containing hydrocarbons is characterized by low Lamda-Rho, Lamda/Mu values and a low Poisson ratio. Porous carbonate layer, characterized by a low Mu-Rho value. The slice results show that the gaseous area is located on the anticline. The zone that has good porosity indicated by low Mu-Rho. In the IN-3 well there are no hydrocarbons, this analysis is in accordance with the geological condition of the IN-3 well which is in a low area on the time structure map. The inversion results show a good match between CPEI against water saturation log and CPEI against porosity log.

Viscoelastic Fluid Factor Inversion and Application in Luojia Oilfield Based on Broadband Impedance

Based on the physical quantity of log data, the accurate identification of oil- and gas-bearing properties may be caused by the prestack inversion of fluid prediction, which will affect the success rate of exploration and development. Prestack data contain more information of amplitude and frequency. Using the frequency-dependent viscoelastic impedance equation and Bayesian inversion framework, the objective function of frequency-dependent elastic impedance inversion can be established to realize the frequency-dependent impedance inversion at different angles. According to the elastic impedance equation of the frequency-varying viscoelastic fluid factor, the relationship between elastic impedance and the frequency-dependent viscoelastic fluid factor is established, and the prestack seismic inversion method of the frequency-dependent viscoelastic fluid factor is studied. However, one of the important factors easily neglected is that we have been using logging data to establish fluid-sensitive parameters and the lithophysical version for fluid identification, so there are differences between logging and seismic frequency bands for fluid identification. The indicator factors with higher sensitivity to fluid can be selected by laboratory measurements. This article applies this method on Luojia oilfield data and verifies this method with log interpretation results, based on the sample of rock physics obtained in a low-frequency rock physics experiment; the technique of dispersion and fluid-sensitive parameters is studied, and the fluid prediction technology of a multifrequency band rock physics template is adopted, which can build the relationship between rock physical elastic parameters and fluid properties by the multifrequency broadband impedance method.

Hydrocarbon reservoir delineation using simultaneous and elastic impedance inversions in a Niger Delta field

The global energy demand is increasing while production from mature fields is drastically reducing consequently, oil and gas industries are expanding activities into more challenging areas. The inability of the traditional seismic data to properly delineate hydrocarbon reservoirs from subtle seismic features in ‘Sandfish’ field located offshore, Niger Delta informed the use of simultaneous and elastic impedance inversion. The elastic and derived volumes from seismic inversion would reduce risk, enhance hydrocarbon discovery and optimize development plans in the study area. Four ‘Sandfish’ (Sfn) wells (Sfn-01, Sfn-02, Sfn-04 and Sfn-05), check-shots and 3D seismic data of five angle stacks (6–12°, 12–18°, 18–26°, 26–32° and 32–42°) were used in the study. Low frequency (0–2 Hz) models were generated from interpolation of high-cut-filtered compressional wave velocity log (P-sonic), shear wave velocity log (S-sonic) and density log guided by interpreted four seismic horizons. The low frequency models broaden the spectrum of the elastic volumes and also served as inversion constraints. The five partial angle stacks varying from 6–42° were simultaneously inverted using Jason’s Rock-Trace® inversion software which iterated trial inversions until the model sufficiently matched the seismic data. The near (6–12°) angle and far-far (32–42°) angle stacks were also inverted and compared with the inverted volumes from the simultaneous inversion. This was carried out to determine the effectiveness of near and far-far elastic impedance volume in delineating hydrocarbon reservoirs. The inverted elastic volumes P-impedance (ZP), S-impedance (ZS), density (ρ), near and far-far elastic and derived volumes lambda-rho (λρ), mu-rho (µρ), Poisson’s-ratio (σ) reveal vertical and lateral continuity of the reservoirs identified (K01, N01 and P01) at 2179 m, 2484 m and 3048 m, respectively. The delineated reservoirs showed good match with the sand tops away from the well control validated by a blind well test. The cross-plot of inverted ZP from simultaneous inversion and well ZP gave correlation coefficient of 86% indicative of high quality inverted volume which will reduce exploration risk. The plot of inverted ZP from simultaneous inversion and inverted far-far elastic volume reflected 82% correlation coefficient indicating that this method could be adopted in other fields with limited data and similar geological setting. Hence, the study has shown the efficacy of elastic volumes in delineating hydrocarbon reservoirs which can help locate optimum region for development wells.

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

An integrated workflow is proposed for estimating elastic parameters within the Late Triassic Skagerrak Formation, the Middle Jurassic Sleipner and Hugin Formations, the Paleocene Heimdal Formation and Eocene Grid Formation in the Utsira High area of the Norwegian North Sea. The proposed workflow begins with petrophysical analysis carried out at the available wells. Next, model-based prestack simultaneous impedance inversion outputs were derived, and attempts were made to estimate the petrophysical parameters (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 employed for defining different facies in the intervals of interest.

Extended Elastic Impedance Inversion for Better Delineation of Gasbearing Sand Reservoir, Saffron Gas Field, Offshore Nile Delta, Egypt

Extended Elastic Impedance (EEI) is a very useful seismic reconnaissance attribute. EEI logs can directly correspond to the petrophysical properties of the reservoir and the seismic. EEI reflectivity volumes can be obtained directly from the pre-stack seismic data. Better discrimination between the seismic anomaly caused by either lithology or fluid content can be utilized by applying this approach. The concept of extended elastic impedance is used to derive the petrophysical properties and distribute the reservoir facies. The study area was a Pliocene gas field, that lies in the deep marine, Offshore Nile Delta, Egypt. The workflow is simple, efficient, and uses very few inputs. We started with the fluid/ lithology logs and investigated the optimum projection in the intercept/gradient domain. Then, we used the conditioned angle stacks, to calculate the intercept/ gradient volumes, using Shuey’s two-term Approximation. The intercept and gradient volumes are converted directly to the fluid and lithology 3D volumes, without any of the pre-stack inversion constraints. The outputs were tested using a blind well and the correlation exceeds 80%. The results show that the EEI is a worthy effort to highlight the difference between the reservoir and nonreservoir sections, to identify the hydrocarbon area.