AVO analysis aids in differentiation between false and true amplitude responses: a case study of El Mansoura field, onshore Nile Delta, Egypt
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The seismic amplitude versus offset (AVO) analysis has become a prominent in the direct hydrocarbon indicator in last decade, aimed to characterizing the fluid content or the lithology of a possible reservoir and reducing the exploration drilling risk. Our research discusses the impact of studying common depth point gathers on Near, Mid and Far-offsets, to verify the credibility of the amplitude response in the prospect evaluation, through analyzing a case study of two exploratory wells; one has already penetrated a gas-bearing sandstone reservoir and the second one is dry sand, but drilled in two different prospects, using the AVO analysis, to understand the reservoir configuration and its relation to the different amplitude response. The results show that the missing of the short-offset data is the reason of the false anomaly encountered in the dry sand, due to some urban surface obstacles during acquiring the seismic data in the field, especially the study area is located in El Mansoura city, which it is a highly cultivated terrain, with multiple channels and many large orchards on the edge of the river, and sugar cane and rice fields. Several lessons have been learned, which how to differentiate between the gas reservoirs and non-reservoirs, by understanding the relation between the Near and Far-offset traces, to reduce the amplitude anomalies to their right justification, where missing of Near-offset data led to a pseudo-amplitude anomaly. The results led to a high success of exploration ratio as the positives vastly outweigh the negatives.
KeywordsAmplitude anomaly CDP gathers AVO analysis Seismic inversion Compressional wave Shear wave
AVO classification and processing
The seismic data amplitudes must be preserved, to detect the amplitude variation with offset.
The broadband signal has to be kept with a flat spectrum.
Pre-stack inversion should be applied to the CDP gathers, to produce the different attributes.
Wavelet and seismic tie
Super gather (common-offset gather)
The velocity data used in our research have been derived from the well data. Another benefit is the generation of super and angle gathers is to plot the offset against the incidence angles in order to verify the limit of the far offset or far angles that can be trusted.
AVO reflectivity attributes and interpretation
Pre-stack seismic inversion
Seismic inversion is converting the seismic data to a measurable rock-properties or fluid contents useful as for the hydrocarbon reservoirs (Hampson et al. 2005). It involves extraction of acoustic impedance from seismic data (P-impedance the product of the density and P-wave velocity) that help to make predictions of important reservoir properties like lithology and porosity. Inversion as indicated from the name is the inverse of a model of the earth properties, then mathematically simulates physical properties on earth model and outputs a modeled response. If assumptions and the adopted model are accurate, the output should be a replica to the real data. Conversely, inversion begins with a recorded seismic data trace then gets rid of the effect of an estimated wavelet, and then at every time sample we create values of acoustic impedance (Barclay et al. 2008).
Building the pre-stack inversion model
Logs correlation with seismic/wavelet extraction.
An initial impedance model.
Integrate both seismic data and log data.
- Pre-stack inversion analysis (Fig. 15).
Precise estimate of wavelet for calculating synthetic for the seismic inversion success and likewise relies on a perfect tie between the well to seismic. As the wavelet shape has effects in the inversion results, subsequent assessment of the reservoir management is dependent to the selected wavelet (Barclay et al. 2008).
Results and discussion
Limitations and uncertainties in AVO applications
We use the AVO as a tool for recognizing and validating the presence of hydrocarbons, reducing the risk of drilling a dry hole or passing over a profitable discovery. However, we find there are several pitfalls during the application, due to the limitation of the technique, caused by misleading data, complex lithology combinations and thickness variations.
Non-commercial gas saturation
Traditional 2-term AVO will not be able to discriminate between a seismic anomaly caused by a few percent gases and an anomaly caused by commercial amounts of hydrocarbon. This is a universal problem and many wells have been drilled on AVO driven prospects that indicated hydrocarbons, but proved to be residual amounts of gas. These were scientifically correct, but commercial failures. 3-terms AVO calculating density, to estimate gas saturation, is based on the linear behavior of density with gas saturation. However, uncertainty factors, such as the poor signal-to-noise ratio and the effect of anisotropy at mid to far offsets make the 3-terms AVO difficult.
Data quality problem
Seismic artifacts can cause a false AVO anomaly. Unfavorable acquisition conditions can lead to data problems, which can be seen in El Mansoura area, such as weak/no signal at the Near-offsets, due to the limited data fold, noisy Far-offset, or weak/no reflection for some deeper formations. Some problems are processing related, such as the Far-offset high amplitude and low frequency by NMO, residual move-out, and offset dependent amplitude scaling and poor application of data muting.
During the AVO application in the study area, find the chance of success is generally higher in the clastic sand/shale environment, rather than carbonate the environment. Modeling found the high amplitude is more likely, a lithology indictor than the fluid indictor in limestone environment.
The weak seismic coverage has been affected on the seismic amplitude anomaly reliability, structure geometry and the AVO response with offset. So, the analysis of the CDP gathers on different angles, verification of the AVO response can help in evaluate the potentiality of the prospects and determine the response of the seismic amplitude variation with the offset. The AVO analysis and pre-stack modeling allow the interpreter to: (1) Understanding the seismic signature, due to the wave propagation. (2) Defining the reservoir rock physical properties. (3) Integrating seismic, well logs, lab testing and VSP information, to verify the reservoir conditions. Pre-stack modeling is effective to:
(a) Examining the seismic response, due to lithology’s physical properties, such as porosity, fluid content and reservoir and pay thickness. (c) Substituting the pore fluid and modeling the seismic response. (d) Varying the reservoir properties and model the seismic response. (e) Exploring the uniqueness of possible seismic interpretation. (f) Evaluating the exploration potential and recognizing the exploration risk. (g) Processing the synthetic gather, to extract attributes to understand, which may be useful.
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