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Reservoirs are often layered, and the seismic AVO response through these layers is frequency dependent and complex. Traditional AVO analysis uses only amplitude and assumes isolated thick layers. Here we exploit both amplitude and phase in our analysis. The frequency dependent AVO (FAVO) response is a function of layer thicknesses and their rock and fluid properties. To exploit the FAVO response due to subtle changes in reservoir properties, we propose a new method to derive a reflectivity seismic volume from an input seismic volume. We then estimate frequency dependent AVO intercept, gradient, and curvature; and calculate P-wave velocity, S-wave velocity, and density reflectivities. These FAVO attributes can be used for quantitative reservoir interpretation. We demonstrate the proposed method with synthetic models.
Presentation Date: Tuesday, October 16, 2018
Start Time: 8:30:00 AM
Location: 206A (Anaheim Convention Center)
Presentation Type: Oral
Konings, Stijn Pieter Marie (Kosmos Energy LLC) | Hyde, Emma (Kosmos Energy LLC) | Noah, Jesse (Kosmos Energy LLC) | Schneider, Rhys (Kosmos Energy LLC) | Groves, Lee (Kosmos Energy LLC) | Deina, Chemsdine Sow (SMHPM)
In April 2015 Kosmos Energy discovered the Ahmeyim (formerly Tortue) gas field, followed by the discovery of the Bir Allah (formerly Marsouin) gas field, opening a new hydrocarbon province offshore Mauritania outboard of the proven upper slope salt play. Ahmeyim and Bir Allah encountered Cenomanian and Albian sands in a middle to lower slope setting. The hydrocarbon bearing sands exhibit strong anomalous class 2 AVO (Amplitude Versus Offset) response relative to the background while the water sands do not. Interrogation of the well data reveals well constrained rock physics models for both reservoir sands, as well as the background shales. Narrow uncertainty ranges in the relationships between the elastic parameters constituting the rock physics models allow for the construction of accurate forward synthetic AVO models. Comparison of these models to seismic AVO and migration velocity observations has successfully helped to reduce the pre-drill risk on reservoir presence, reservoir quality and reservoir fluid content. Confirmation of the models by consecutive wells has increased confidence in this exploration tool, but one should always remain cautious for unforeseen scenarios.
Presentation Date: Tuesday, September 26, 2017
Start Time: 2:40 PM
Presentation Type: ORAL
The result is that the source statics for the Sv-The demonstrated presence of Sv-P reflections on regular P reflections are very large and problematic. The shear P-wave data, with P-wave sources (vertical vibrators, uphole time for buried explosives is not available.
Second, Coalbed methane content (CBMC) is an important there is difference of Poisson's ratio between water parameter for coalbed methane (CBM) development, and saturated coal seam and gas saturated coal seam. It is not coalmine gas drainage. CBMC prediction by 3D seismic proper for coal seam, because CBM is mainly in the state of amplitude is still one of the issues to be discussed, because adsorption, water saturated coalbed doesn't means that it is the adsorption characteristics of CBM make the Gassmann less CBMC. Then Gassmann equations can't describe it equation no effect for coal seam. Here I try to directly (Chen et al, 2013). So, the second base is set as there is construct the relationship between CBMC and amplitude difference of Poisson's ratio between different gas content versus offset (AVO) attributes, so as to establish the of coal seams. If it is true in real situation, it is possible to foundation for further work.
The rocks in this younger Tertiary basin are generally soft, unconsolidated and are sensitive to fluid replacement and response as per Gassmann. Hence, quantitative AVO plays a significant role in hydrocarbon prediction (Ghosh et al., 2014). It was found that the vast majority (70%) of pay zone have Class II AVO types in the Peninsular Malay basin. However, wet sands also can give Class II AVO response in some cases, which causes ambiguous results. In order to obtain more accurate results, we use spectra cross plot technique which combines AVO and spectral decomposition. This technique is a quick and useful way to discrimination between gas and wet sands (Ren et al. 2007). This study attempts to apply spectral cross plot technique in a field of Malay basin to improve the performance of AVO.
CRP gathers after PSTM (Prestack Time Migration ) with residual multiples heavily spoil the precision of pre-stack inversion , especially residual multiples which occur at the near offsets are extremely difficult to attenuate and therefore lead to distortion for interpretation , Conventional Radon filtering based on the velocity variation, which can make the moveout of the primary and the multiple different after NMO, will not be able to work because residual moveout at the near offsets become so small that multiples at near offsets are not often easy to separate from the primaries . In this paper a method based on AVO is used to suppress the residual multiples at the near offsets, which performs very well in attenuating these remnant multiples by applying this method to both synthetic models and field data.
As for marine data multiple attenuation is the key of seismic data processing due to the fact that multiples severely contaminate the information which primary reflection can give about the real subsurface structure and therefore cause ambiguities in reservoir identification and fluid detection.
As mentioned above, the parabolic Radon transform can effectively eliminate most multiples at the middle and far offsets where the moveout difference between the primaries and multiples after NMO can be discriminated. However, after Radon demultiple processing the residual multiples still remain at near offsets (Hunt, 1996; Hargreaves, 2001). Another demultiple method based on wavefield prediction and subtraction such as SRME can easily suppress the multiples associated with the free surface, the great advantage of SRME is that no subsurface information is required, the price SRME must pay is that in order to properly predict the multiples, all the needed subevents must be recorded, missing near offsets in which all free surface multiples cannot be predicted are a crucial issue, in practice, the missing near offsets usually are extrapolated (Berkhout and Verschuur, 1997).
CRP gathers without residual multiples at near offsets can be obtained by taking full advantage of AVO which can generate a forward modeling gather. In this paper, we improve this method in a way that an inner mute library is deliberately designed in order to perfectly remove the residual multiples at near offsets. Synthetic data and field datasets demonstrate that this newly reformed method are capable of effectively suppressing the residual multiples at near offsets.
Amplitude-variation-with-offset (AVO) inversion is a routinely used practice for reservoir characterization. Although it has been quite successful, reservoir geophysicists do realize its shortcomings and for any quantitative estimation of reservoir properties, AVO inversion results are always interpreted in combination with other information. On the other hand, waveform based inversion methods are now slowly gaining popularity in both reservoir characterization and depth imaging applications. Going beyond the simple assumptions of AVO and employing exact solution to the wave equation, these methods have been shown to be quite effective in accurately predicting the subsurface properties. Routine application of waveform based inversion is however, still computationally prohibitive. In this work we describe an elastic waveform inversion methodology in a distributed and parallel computing environment that allows its applications in a reasonable timeframe. Applying AVO and waveform inversion on a single data set from the Rock-Springs Uplift (RSU), Wyoming USA, and comparing them with one another in combination with the RSU geology, we also demonstrate that the waveform inversion is capable of obtaining much superior description of subsurface properties compared to AVO. We conclude that the waveform inversion should be the method of choice for reservoir property estimation as large high-performance computers become commonly available.
This study involves delineation of geophysical properties of a small region in Scotian Basin, offshore Nova Scotia, Canada. In this study, three different geophysical methods were applied to evaluate the Abenaki formation for hydrocarbon potential using quantitative geophysical methods. These methods are AVO, prestack impedance inversion and poststack impedance inversion. AVO modeling/analysis is a technique used to infer fluid content and lithology variations by studying the amplitude variations at a layer boundary in the CDP gather. Seismic inversion methods are used to characterize geophysical properties within layers. The use of AVO, prestack simultaneous impedance inversion, and poststack model-based impedance inversion lead to a robust interpretation.
In this study, it is observed that AVO method is inadequate itself to explain either change in lithology or fluid content causes AVO variations. Using prestack inversion and poststack inversion methods, subsurface lithology or fluid change can be evaluated by means of seismic velocities in an effective manner.
Wright, Richard (Nalcor Energy Oil and Gas) | Carter, James (Nalcor Energy Oil and Gas) | Cameron, Deric (Nalcor Energy Oil and Gas) | Neugebauer, Tom (TGS) | Witney, Jerry (PGS) | Hughes, Daniel (Astrium Services)
The survey GeoStreamer seismic survey spanning the Canadian was planned integrating well ties from the shelf, regional Labrador Sea from the shelf edge to the Canada-Greenland gravity data, and newly acquired satellite slick data that border as shown in Figure 1. Due to large areal coverage suggested the potential for oil prone hydrocarbon systems and the coarse spacing of the lines (average 60 x 60 km in the previously unexplored deepwater areas. The early grid), optimal line placement was a primary consideration data results from this initial 2011-2012 program (22,000 and utilized well ties, regional gravity data, and satellite line km) are encouraging and have resulted in the slick data.
SummaryThe gas reservoirs in the Zhujiangkou basin are complex, and therefore challenge traditional techniques in predicting the location and abundance of hydrocarbons. In order to better characterize the reservoirs, and achieve higher success in their exploration, in this paper, we use rock physics and AVO to thoroughly analyze the reservoirs in the study area. Based on the analysis, pre-stack inversion is used to characterize the reservoirs and identify the fluid. The results of our analysis demonstrate that density is a good attribute to detect zones of interest in our study area, and it can differentiate the reservoirs saturated with gas and water, respectively.