Variations of reflection amplitude with offset and azimuth are sensitive to the presence of natural and induced fractures. For a transversely isotropic media with titled symmetry (TTI), the components of the normal and tangential weaknesses of the fracture system can be used as attributes related to the characteristics of the fractured medium. In this paper, we derive a new approximate formula for the analysis of the relationship between fracture weakness and reflection amplitude. Using this formula, we use synthetic azimuthal seismic data to invert the elastic and fracture weaknesses of TTI media based on AVAZ inversion. The damped least squares method, which uses the estimated results from well-logging data as initial constraints during the inversion, is more stable. Tests on synthetic data show that fracture weaknesses parameters are still estimated reasonably with moderate noise.
Presentation Date: Wednesday, September 27, 2017
Start Time: 9:20 AM
Location: Exhibit Hall C/D
Presentation Type: POSTER
Huang, Guangtan (China University of Petroleum-Beijing) | Li, Jingye (China University of Petroleum-Beijing) | Luo, Cong (China University of Petroleum-Beijing) | Chen, Xiaohong (China University of Petroleum-Beijing)
In exploration geophysics, AVO inversion is one of the most common inverse problems, which is ill-posed and usually be solved by regularization. However, once regularization is used, the selection of regularization parameter will become a critical problem to be solved. In practice, the regularization parameter value is usually data dependent and determined empirically. For one work area, inversion engineers often give a fixed parameter. In such a case, the results of AVO inversion will be accompanied by strong artificial subjective factors. Moreover, it is difficult to guarantee that the fixed parameter could be applied to each trace of the seismic data. In this abstract, based on traditional Generalized cross validation (GCV) criterion, we proposed an adaptive acquisition regularization parameter method which can be used for arbitrary norm as regularization condition. Then, applying this method to the AVO inversion of synthetic data and field data, we found that the improved GCV method has better accuracy and robustness than the traditional method.
Presentation Date: Monday, September 25, 2017
Start Time: 3:55 PM
Location: Exhibit Hall C, E-P Station 3
Presentation Type: EPOSTER
Owing to the different attenuation mechanism of the mudstone and sandstone, different rock physical models should be chosen according to the actual situation in the establishment of thin interbed model. In this abstract, we used Carcione viscoelastic VTI model to simulate shale, patch saturation model and Chapman multi-scale fracture model to simulate gas-bearing sandstone with and without fractures respectively. Then, abandoned the conventional AVO forward modeling method based on Zoeppritz equation, we introduced generalized propagation matrix method to the frequency-dependent AVO (FAVO) analysis in the stratified media. This method effectively overcome the assumption of Zoeppritz equation, i.e., infinite half space elastic media. Results of numerical simulation indicate that layer thickness and fluid saturation are the key factors to the FAVO effect. Meanwhile, for the anisotropic sandstone, fractures are also the important factors to reflections in the presence of dispersion and attenuation, but the effects of fractures are mainly reflected in the large angle. The variations of fracture density, aspect ratio and scale will cause the change of the FAVO response.
Presentation Date: Tuesday, September 26, 2017
Start Time: 4:45 PM
Presentation Type: ORAL
Song, Wei (China University ofPetroleum–Beijing) | Liu, Guochang (China University ofPetroleum–Beijing) | Li, Jingye (China University ofPetroleum–Beijing) | Chen, Xiaohong (China University ofPetroleum–Beijing)
Widening the range of frequencies in the seismic dataset is broadly acknowledged for its contribution to imaging quality, so extra octaves of signals have to be generated. But the high frequency component of seismic signal acquired using conventional vibroseis is affected by absorption and attenuation of near surface layer. The bandwidth of seismic data is relatively narrow in complex attenuation media, which affects the resolution of seismic imaging. A nonlinear sweep adaptive vibrator acquisition is designed and the high frequency component can be compensate adaptively. But the main problem is how to determine the nonlinear adaptive vibrator parameters according to the characteristics of near surface layer. This abstract presents and discusses a new practical and effective solutions to push the frequencies emitted by nonlinear sweep adaptive vibrators higher.
Presentation Date: Thursday, September 28, 2017
Start Time: 11:00 AM
Presentation Type: ORAL
Chen, Rukang (China University of Petroleum–Beijing) | Chen, Xiaohong (China University of Petroleum–Beijing) | Li, Jingye (China University of Petroleum–Beijing) | Wang, Zhikai (China University of Petroleum–Beijing) | Wang, Benfeng (Tsinghua University)
The direct hydrocarbon detection with seismic data is a difficult and longstanding problem. Numerous fluid indicators derived from linearized Zoeppritz equation have been published, which provide a good tool to identify hydrocarbon zones. But the question of which is these indicators take less advantages of frequency-dependent properties. In essence, rocks saturated with gas show high attenuation and wave dispersion, so the hydrocarbon indicators based on the frequency of the reflections can be used to improve estimation accuracy of hydrocarbon zones. In this abstract, we propose a new frequency-dependent indicator, which is derived from linearized FAVO inversion and traditional AVO methods. We apply this scheme to a real seismic data, and the results demonstrate that this new indicator can more accurately discriminate the gas/oil sand from the background and is also less sensitive to random noise and the accuracy of spectrum decomposition.
Presentation Date: Monday, October 17, 2016
Start Time: 3:20:00 PM
Presentation Type: ORAL
Chen, Yangkang (University of Texas–Austin) | Xiang, Kui (China University of Petroleum–Beijing) | Chen, Hanming (China University of Petroleum–Beijing) | Chen, Xiaohong (China University of Petroleum–Beijing)
Full waveform inversion (FWI) is a promising technique for inverting a high-resolution subsurface velocity model. The success of FWI highly depends on a fairly well initial velocity model. We propose a method for building a remarkable initial velocity model that can be put into the FWI framework for inverting nearly perfect velocity structure. We use a well log interpolated velocity model as a high-fidelity initial model for the subsequent FWI. The interpolation problem is solved via a least-squares method with a structural regularization. In order to obtain the geological structure of subsurface reflectors, an initial reverse time migration (RTM) with a fairly realistic initial velocity model is used to roughly calculate the local slope of subsurface structure. The well log interpolated initial velocity model can be very close to the true velocity while having small velocity anomaly or over-smoothing caused by the imperfect velocity interpolation, which however can be compensated during the subsequent FWI iterations. Regarding the field deployment, we suggest that future drilling should be seismic-oriented, which can help fully utilize the well logs for building initial subsurface velocity model and will facilitate a wide application of the proposed methodology.
Presentation Date: Wednesday, October 19, 2016
Start Time: 4:25:00 PM
Presentation Type: ORAL
Chen, Yangkang (University of Texas—Austin) | Xiang, Kui (China University of Petroleum—Beijing) | Chen, Hanming (China University of Petroleum—Beijing) | Chen, Xiaohong (China University of Petroleum—Beijing)
The simultaneous-source shooting technique can accelerate field acquisition and improve spatial sampling but will cause strong interferences in the recorded data. Direct imaging of blended simultaneous-source data has been demonstrated to be a promising research field since there is no need to separate the blended data before the subsequent processing and imaging. The key issue in direct imaging of blended data is the strong artifacts in the migrated image. Although the least-squares migration can help reduce some artifacts, there are still residual artifacts in the image. Those artifacts mainly appear in the shallow part of the image as spatially incoherent noise. Previously proposed structural smoothing operator can effectively attenuate the artifacts for relatively simple reflection structures during least-squares inversion, but it will cause damage to complicated reflection events such as the discontinuities. In order to preserve the discontinuities in the seismic image, we apply the singular spectrum analysis (SSA) operator to attenuate artifacts during least-squares inversion. Considering that global SSA cannot deal with over-complicated data well, we propose to use local SSA in order to remove noise and preserve steeply dipping components better. The local SSA operator corresponds to a local low-rank constraint applied in the inversion process. The migration operator used in the study is the reverse time migration (RTM) operator. We use the Marmousi model example to show the superior performance of the proposed algorithm.
Presentation Date: Wednesday, October 19, 2016
Start Time: 11:35:00 AM
Presentation Type: ORAL
Projection Onto Convex Sets (POCS) method is an efficient iterative method for seismic data interpolation. In each iteration, observed seismic data is inserted into the updated solution, therefore it has difficulty for interpolation in noisy situations. Weighted POCS method can weaken the noise effects because it uses a weight factor to scale the observed seismic data, then fewer noisy data is inserted into the updated solution, but it still inserts some random noise. In this abstract, a novel method is proposed by combining the advantages of the weighted POCS method and the Iterative Hard Threshold (IHT) method: the weighted POCS method used for interpolation and the IHT method used for random noise elimination. The novel method can be used for simultaneous interpolation and random noise removal of seismic data, and its validity is demonstrated on synthetic and real datasets.
Spatial irregularity and random noise observed in seismic data can affect the performance of Surface-Related Multiple Elimination (SRME), wave-equation based migration and inversion. Therefore, interpolation and random noise elimination is pre-requisite for multi-channel processing techniques.
Interpolation methods can be divided into four categories (Gao et al., 2012; Wang et al., 2014): mathematical transform based methods, prediction filters based methods, wave-equation based methods and rank-reduction based methods. Among these methods, mathematical transform based methods are easy to implement and have drawn much attention. While the random noise in observed seismic data can affect the interpolation performance and the irregularity of observed data can also affect the results of random noise elimination. Therefore, simultaneous interpolation and random noise attenuation is developed (Naghizadeh, 2012; Oropeza and Sacchi, 2011), while it is suitable for linear or quasi-linear events and should be handled window by window for curved events.
Gan, Shuwei (China University of Petroleum, Beijing) | Wang, Shoudong (China University of Petroleum, Beijing) | Chen, Yangkang (The University of Texas at Austin) | Chen, Xiaohong (China University of Petroleum, Beijing)
The distance separated simultaneous sourcing technique can make the interference between different source smallest. In a distance separated simultaneous-source acquisition system with two sources, we propose to use a novel iterative seisletframe thresholding approach to separate the blended data. Because the separation is implemented in common shot gathers, there is no need for the random scheduling that was used in conventional simultaneous-source acquisition, where the random scheduling is applied to ensure the incoherent property of blending noise in common midpoint, common receiver, or common offset gathers. Thus, the distance separated simultaneous sourcing becomes more flexible. The separation is based on the assumption that the local dips of the data from different sources are different. We can use plane-wave destruction (PWD) operator to simultaneously estimate the conflicting dips and then use seislet frames with two corresponding local dips to sparsify each signal component. The interference becomes unpredictable noise in the dip-governing seislet transform domain and can thus be removed by soft thresholding. A simulated field data example shows excellent performance of the proposed approach.
The principal purpose of simultaneous source acquisition is to faster the acquisition of a larger-density seismic dataset, which saves numerous acquisition cost and increases data quality. The benefits are compromised by the intense interference between different shots (Berkhout, 2008). One way for solving the problem caused by interference is by first-separating and second-processing strategy (Chen et al., 2014a), which is also called deblending (Moore et al., 2008; Akerberg et al., 2008; Moore, 2010; Abma et al., 2010; Huo et al., 2012; Mahdad et al., 2011; Blacquiere and Mahdad, 2012; Beasley et al., 2012; Doulgeris et al., 2012; Mahdad et al., 2012; Bagaini et al., 2012; Li et al., 2013; Chen and Ma, 2014; Chen et al., 2014b; Berkhout and Blacquiere, 2014; Chen, 2014). Another way is by direct imaging and inversion of the blended data by attenuating the interference during inversion process (Verschuur and Berkhout, 2011; Dai and Schuster, 2011; Xue et al., 2014; Chen et al., 2015). Currently, deblending is still the dominant way for dealing with simultaneous-source data.
We propose to use a structural-oriented median filter to attenuate the blending noise along the structural direction. The principle of the proposed approach is to first flatten the seismic record in local spatial windows and then to apply a traditional median filter (MF) to the third flattened dimension. The key component of the proposed approach is the estimation of the local slope, which can be calculated by first scanning the NMO velocity and then transferring the velocity to the local slope. Both synthetic and field data examples show successful performance using the proposed approach.
The principal purpose of simultaneous source acquisition is to faster the acquisition of a larger-density seismic dataset, which saves numerous acquisition cost and increases data quality. The benefits are compromised by the intense interference between different shots (Berkhout, 2008). One way for solving the problem caused by interference is by first-separating and second-processing strategy (Chen et al., 2014a), which is also called deblending (Akerberg et al., 2008; Abma et al., 2010; Huo et al., 2012; Mahdad et al., 2011; Blacquiere and Mahdad, 2012; Beasley et al., 2012; Doulgeris et al., 2012; Mahdad et al., 2012; Bagaini et al., 2012; Li et al., 2013; Chen and Ma, 2014; Chen et al., 2014b; Berkhout and Blacquiere, 2014; Chen, 2014). Another way is by direct imaging and inversion of the blended data by attenuating the interference during inversion process (Verschuur and Berkhout, 2011; Dai and Schuster, 2011; Xue et al., 2014; Chen et al., 2015). Currently, deblending is still the dominant way for dealing with simultaneous-source data.