Application of four-component dipole shear reflection imaging to interpret the geological structure around a deviated well

Acoustic reflection imaging in deep water wells is a new application scope for offshore hydrocarbon exploration.Two-dimensional(2 D)geological structure images can be obtained away from a one-dimensional(1 D)borehole using single-well acoustic reflection imaging.Based on the directivity of dipole source and four-component dipole data,one can achieve the azimuth detection and the three-dimensional(3 D)structural information around the wellbore can be obtained.We first perform matrix rotation on the field fourcomponent data.Then,a series of processing steps are applied to the rotated dipole data to obtain the reflector image.According to the above dipole shear-wave imaging principle,we used four-component cross-dipole logging data from a deviated well in the South China Sea to image geological structures within 50 m of a deviated well,which can delineate the structural configuration and determine its orientation.The configuration of near-borehole bedding boundaries and fault structures from shear-wave imaging results agrees with those from the Inline and Xline seismic profiles of the study area.In addition,the configuration and orientation of the fault structure images are consistent with regional stress maps and the results of the borehole stress anisotropy analysis.Furthermore,the dip azimuth of the bedding boundary images was determined using borehole wall resistivity data.Results of this study indicate that integrating borehole acoustic reflection with seismic imaging not only fills the gap between the two measurement scales but also accurately delineates geological structures in the borehole vicinity.

Least-squares reverse time migration method using the factorization of the Hessian matrix

Least-squares reverse time migration(LSRTM)can eliminate imaging artifacts in an iterative way based on the concept of inversion,and it can restore imaging amplitude step by step.LSRTM can provide a high-resolution migration section and can be applied to irregular and poor-quality seismic data and achieve good results.Steeply dipping refl ectors and complex faults are imaged by using wavefi eld extrapolation based on a two-way wave equation.However,the high computational cost limits the method’s application in practice.A fast approach to realize LSRTM in the imaging domain is provided in this paper to reduce the computational cost signifi cantly and enhance its computational effi ciency.The method uses the Kronecker decomposition algorithm to estimate the Hessian matrix.A low-rank matrix can be used to calculate the Kronecker factor,which involves the calculation of Green’s function at the source and receiver point.The approach also avoids the direct construction of the whole Hessian matrix.Factorization-based LSRTM calculates the production of low-rank matrices instead of repeatedly calculating migration and demigration.Unlike traditional LSRTM,factorization-based LSRTM can reduce calculation costs considerably while maintaining comparable imaging quality.While having the same imaging eff ect,factorization-based LSRTM consumes half the running time of conventional LSRTM.In this regard,the application of factorization-based LSRTM has a promising advantage in reducing the computational cost.Ambient noise caused by this method can be removed by applying a commonly used fi ltering method without signifi cantly degrading the imaging quality.

Linear inversion-imaging method based on joint primary refl ected waves and surface-related multiples

In marine seismic exploration,especially in deep-water and hard ocean-bottom cases,free-surface multiples are strongly developed.Compared with primary waves,the wider illumination aperture of the multiples is beneficial for high-resolution seismic imaging.In this study,by introducing a new compound source composed of primaries and free-surface multiples and by ignoring internal multiples,we derive a new linearized forward problem(free-surface-multiple prediction model)under a weak-scattering assumption(i.e.,first-order Born approximation).On the basis of the new linearized problem,we propose a joint inversion-imaging method by simultaneously using the primaries and free-surface multiples under the general framework of least square inversion.To eliminate the crosstalk artifacts introduced by the cross-correlation of multiples with different orders,we prove that the crosstalk artifacts can be gradually eliminated during the inversion if a proper step length is selected.Synthetic-andfield-data tests demonstrate the effectiveness of the proposed method.