The development of seismic reflection sandbox modeling

Abstract

Analog sandbox models provide cheap, concise data and allow the evolution of geological structures to be observed under controlled laboratory conditions. Seismic physical modeling is used to study the effects of seismic wave propagation in isotropic and anisotropic media, and to improve methods of data acquisition, processing, and interpretation. By combining these two independent modeling techniques, the potential exists to expand the benefits of each method. For seismic physical modeling, the main advantages are that the seismic data collected from these models contain natural variations that cannot be built into conventional solid models, which are machined with predetermined structures. In addition, the cost and construction time to build these models is significantly reduced. For sandbox modeling, the ability to record threedimensional (3-D) seismic images before the model is manually sectioned for conventional two-dimensional (2-D) structural interpretation allows far more detailed study of subtle 3-D structures than previously possible. In the past other workers have attempted to use unconsolidated sands for seismic physical models, but these attempts have been unsuccessful because of the lack of control or understanding of the natural variations that occur throughout the models. The aim of our research has been to overcome such problems and to develop techniques to alter the acoustic impedance of sand layers, thereby allowing the subsequent ultrasonic seismic recording of 3-D fault systems in sand analog geological models.

Numerical modeling of 3D zero-offset laboratory data by a discretized Kirchhoff integral method

“…But even nowadays, physical modeling is still frequently used for configurations whose response is difficult to model numerically. It has been used to study wave propagation in complex 3D media, such as anisotropic (Stewart et al, 2013), random heterogeneous (Sivaji et al, 2002), dynamic (Sherlock and Evans, 2001), fractured (Ekanem et al, 2013), or anelastic (Lines et al, 2012) media. Data from laboratory experiments are considered as input data in inverse problems (Pratt, 1999), for testing new data processing algorithms (Campman et al, 2005), in time-lapse 3D studies (Sherlock et al, 2000), and to benchmark numerical model solutions (Bretaudeau et al, 2011).…”