Research on AVO response correction method in time-frequency-space domain and its application in hydrocarbon detection: A case study from BZ Oilfield, Bohai Bay

Author(s):  
Shengqiang Zhang
2020 ◽  
Vol 8 (1) ◽  
pp. SA49-SA61
Author(s):  
Huihuang Tan ◽  
Donghong Zhou ◽  
Shengqiang Zhang ◽  
Zhijun Zhang ◽  
Xinyi Duan ◽  
...  

Amplitude-variation-with-offset (AVO) technique is one of the primary quantitative hydrocarbon discrimination methods with prestack seismic data. However, the prestack seismic data are usually have low data quality, such as nonflat gathers and nonpreserved amplitude due to absorption, attenuation, and/or many other reasons, which usually lead to a wrong AVO response. The Neogene formations in the Huanghekou area of the Bohai Bay Basin are unconsolidated clastics with a high average porosity, and we find that the attenuation on seismic signal is very strong, which causes an inconsistency of AVO responses between seismic gathers and its corresponding synthetics. Our research results indicate that the synthetic AVO response can match the field seismic gathers in the low-frequency end, but not in the high-frequency components. Thus, we have developed an AVO response correction method based on high-resolution complex spectral decomposition and low-frequency constraint. This method can help to achieve a correct high-resolution AVO response. Its application in Bohai oil fields reveals that it is an efficient way to identify hydrocarbons in rocks, which provides an important technique for support in oil and gas exploration and production in this area.


2013 ◽  
Vol 62 (4) ◽  
pp. 521-532 ◽  
Author(s):  
Samir Avdakovic ◽  
Alma Ademovic ◽  
Amir Nuhanovic

Abstract In this paper, the results of correlations between air temperature and electricity demand by linear regression and Wavelet Coherence (WTC) approach for three different European countries are presented. The results show a very close relationship between air temperature and electricity demand for the selected power systems, however, the WTC approach presents interesting dynamics of correlations between air temperature and electricity demand at different time-frequency space and provide useful information for a more complete understanding of the related consumption.


2021 ◽  
Author(s):  
Farnaz Daneshvar Vousoughi

Abstract Two approaches to identify the relation between hydrological time series (rainfall and runoff) and groundwater level (GWL) were used in the Ardabil plain. In this way, Wavelet-entropy measure (WEM) and wavelet transform coherence (WTC) as two approaches of wavelet transform (WT) were used. WEM have been considered as a criterion for the degree of time series fluctuations and WTC present common time-frequency space. In WEM calculation, monthly rainfall, runoff and GWL time series were divided into three different time periods and decomposed to multiple frequent time series and then, the energies of wavelet were calculated for each sub-series. The result showed WEM reduction in rainfall, runoff and GWL. The reduction of WEM presents the natural fluctuations decrease of time series. The reduction of entropy for runoff, rainfall and GWL time series were about 1.58, 1.36 and 29% respectively, it is concluded that fluctuation reduction of hydrological time series has relatively not more effect on the oscillation patterns of GWL signal. In this regard, it could be concluded that the human activities such as water driving from wells can be played main role in the reduction of GWL in Ardabil plain. WTC findings showed that runoff had most coherence (0.9-1) among the hydrological variables with GWL time series in the frequency bands of 4-8 and 8-16 months.


Author(s):  
Roberto Tomás ◽  
José Luis Pastor ◽  
Marta Béjar-Pizarro ◽  
Roberta Bonì ◽  
Pablo Ezquerro ◽  
...  

Abstract. Interpretation of land subsidence time-series to understand the evolution of the phenomenon and the existing relationships between triggers and measured displacements is a great challenge. Continuous wavelet transform (CWT) is a powerful signal processing method mainly suitable for the analysis of individual nonstationary time-series. CWT expands time-series into the time-frequency space allowing identification of localized nonstationary periodicities. Complementarily, Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) methods allow the comparison of two time-series that may be expected to be related in order to identify regions in the time-frequency domain that exhibit large common cross-power and wavelet coherence, respectively, and therefore are evocative of causality. In this work we use CWT, XWT and WTC to analyze piezometric and InSAR (interferometric synthetic aperture radar) time-series from the Tertiary aquifer of Madrid (Spain) to illustrate their capabilities for interpreting land subsidence and piezometric time-series information.


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