Seismic interferometry, also most commonly referred to as Green’s function retrieval by crosscorrelation, is a technique with many applications, such as the reconstruction of surface seismic, VSP, to Ocean-Bottom data using active or passive data. Due to the impurity of the Green’s function retrieved in the presence of one-sided illumination or intrinsic losses, multidimensional deconvolution (MDD) has emerged as an alternative. The MDD application addresses the limitations by deconvolving the point-spread function from the crosscorrelation result, which removes the source signature, surface-related multiples and takes intrinsic losses into account. The similarity of the inverse problems of interferometry by MDD applied to active and transient passive data makes it an attractive framework to merge the two datasets and retrieve a broadband Green’s function (reflection response). The actual merging is done in the frequency-space domain using simple weighting functions. We carried out numerical validation to merge active and passive body waves using interferometry by MDD in a simplified exploration-style environment. The results indicate that sufficient source illumination is needed as well as sufficient spatial receiver sampling to ensure that wavefields are properly recorded. Also, adequate receiver-line length must be ensured to properly record the low-frequency wavefields and meet the first-Fresnel-zone criterion. The retrieved broadband response is desired for interpretation and seismic inversion purposes. INTRODUCTION Seismic interferometry (SI) is generally known as a technique by which a new seismic response is retrieved by crosscorrelating a recorded seismic responses at two receivers locations. Various authors have shown that replacing the crosscorrelation (CC) by multidimensional deconvolution (MDD) has a number of advantages, including improving the radiation characteristics of the retrieved response and relaxing some of the assumptions, see e.g. Wapenaar et al. (2011). Applications of SI by MDD span a wide range that includes active and passive seismic data with different geometry. Minato et al. (2009) applied SI by MDD to retrieve the impulse responses in a crosswell geometry. Wapenaar et al. (2008b) used it to retrieve the reflectivity response for passive data with irregular source distribution. Broggini et al. (2013) used MDD as an imaging condition. Boullenger & Draganov (2015) applied SI by MDD for reconstructing missing source illumination. Van der Neut et al. (2011) used SI by MDD for data redatuming. Drawbacks of applying SI by MDD is the need for accurate wavefield decomposition and matrix-inversion stabilities. In this abstract we introduce SI by MDD as a scheme to merge active and passive body waves in a bid to retrieve a broader spectrum. Several authors have discussed the importance of extending the bandwidth and adding lower frequencies to seismic reflection data. Carter&Pambayuning (2009) have achieved better seismic to well tie and seismic inversion after bandwidth extension. Ten Kroode et al. (2012) demonstrated the benefit of low frequencies in reducing the sidelobe of the wavelet and potential interference with neighboring events. Fromyr & Reiser (2011) highlighted the role of low frequencies in a broadband signal in improving lithology-fluid prediction and reservoir properties estimation. Next, we use acoustic numerical modeling to demonstrate the use of SI by MDD to merge seismic data. We will analyze the assumptions and conditions needed to achieve the merge and produce the desired broadband response.
|Number of pages||5|
|Journal||SEG Technical Program Expanded Abstracts|
|Publication status||Published - 2016|
|Event||SEG International Exposition and 86th Annual Meeting - Dallas & Kay Bailey Hutchison Convention Center, Dallas, United States|
Duration: 16 Oct 2016 → 21 Oct 2016
Conference number: 86