February 2016 THE LEADING EDGE 141 Special Section: Imaging/inversion: Estimating the earth model Basin-scale integrated earth-model building using rock-physics constraints Abstract Earth modeling plays a decisive role in seismic imaging. Presently, methods such as tomography and full-waveform inver- sion (FWI) are widely used to generate 3D high-resolution velocity models across sedimentary basins. However, given the nonunique nature of the solution, the relative fdelity of these velocity models remains low. Moreover, earth-model building must incorporate a dual strategy. In particular, it must derive a velocity model for migration and yield a series of rock properties such as density, temperature, efective stress, and pore pressure. Tese large-scale, basin-sized rock properties are used for drilling purposes and as an initial model for small-scale reservoir property inversion. Hence, one must inquire: How can we improve an earth model built at basin-scale using seismic data? Traditional workfows will simply convert seismic-derived velocity into rock properties, thereby propagating the uncertainty without ad- dressing the issue. To alleviate this problem and fully exploit the potential of seismic data, an alternate work fow will be discussed. Te new workfow involves using rock physics to link rock properties with velocity, and the physical range of the rock properties is used to constrain velocity when derived from surface seismic data; this way we reinforce the reliability of the fnal earth model. Te application of this new work fow is demon- strated using Gulf of Mexico examples. Introduction Velocity-model building is essential for depth imaging. Curvature in common-image-point (CIP) gathers, obtained from surface seismic, implies there are errors in a velocity model. Tese errors can be reduced through tomography iterations, which update the velocity model. Anisotropy-involved model building has proven critical for, among other things, correcting the vertical velocity error derived assuming isotropy. Tus, it is important to incorporate transverse isotropy (TI) with accurate anisotropy parameters in the velocity model for depth imaging. Te number of parameters in the velocity model increases from one in isotropic media to three in vertical transversely isotropic (VTI) media and fve in tilted transversely isotropic (TTI) media. As a result of the increased number of parameters, the uncertainty in the parameter space also is increased. To accurately determine these parameters, one must assess their allowable physical range. As part of an integrated earth model, Bachrach et al. (2013) correlated anisotropy parameters to velocity through rock porosity and temperature. Doing this might narrow the physical range of anisotropy parameters and yield an initial anisotropy model for tomography. Nevertheless, the uncertainty of the anisotropic parameters depends on the accuracy of the velocity values between the wells. Before we fne-tune velocity through tomography, we must choose a Yangjun (Kevin) Liu 1 , Nader Chand Dutta 2 , Denes Vigh 1 , Jerry Kapoor 1 , Cara Hunter 1 , Emmanuel Saragoussi 1 , Laura Jones 1 , Sherman Yang 1 , and Mohamed Abdelmonem Eissa 1 simple anisotropy model to avoid introducing extraneous values from anisotropy into the velocity. We also must understand the physical range of possible velocity values from various rock-physics principles. Which rock-physics principles can we use to constrain velocity? It is known that for shale-dominated basins, efective stress controls velocity in shales. Te relationship between efective stress and velocity has been used widely to predict pore pressure from shales. By inverting the formula for pore-pressure prediction, we can estimate shale velocity from efective stress, given that a predictive relationship between velocity and efective stress is feasible. In this case, efective stress might equate to overburden stress minus pore pressure (Terzaghi, 1943). Te benefts of estimating velocity from efective stress include capturing a large-scale variation of velocity related to basin-scale fuid fow in geologic settings such as minibasins between salt bodies. For instance, subsalt areas are characterized by lower efective stress from lower overburden stress because salt density is less than that of the surrounding shales. A structurally trapped area could lead to higher pore pressure and, therefore, lower ef- fective stress. In contrast, structurally open areas, such as the base of a syncline or down-dip areas, may manifest higher efective stress due to lower pore pressure (pore fuids migrate up dip). Examples of such stress-related velocities can be observed in well-illuminated tomography velocity models (Petmecky et al., 2009). However, to capture these features for a poorly illuminated area, one must provide more guidance for tomography. Te method we propose to constrain velocity for tomography is to use rock physics to create an integrated earth model including rock properties such as efective stress and pore pressure. We can use petrophysical and drilling data, such as mud weight or forma- tion pressure, to calibrate these rock properties. Hence, the physical range of calibrated rock properties can be captured and converted into a variety of constraints limiting the range of rock velocities. Eventually, these rock velocities will be used as constraints in the tomography-inversion process. The rock-physics model relating velocity with effective stress Te rock-physics model relating shale velocity to efective stress within a basin is shown in Figure 1a. Tis rock-physics model follows a theoretical framework proposed by Dutta et al. (2014) and Dutta (1986), in which mechanical compaction governs the reduction of porosity with increasing efective stress, and chemical compaction governs the changes in shale mineral content (shale diagenesis) due to increasing temperature and rock age. In Figure 1a, the relationship between velocity and efective stress is denoted by a diagenesis coefcient β. For younger shales 1 Schlumberger. 2 Consulting geophysicist. http://dx.doi.org/10.1190/tle35020141.1. Downloaded 11/16/17 to 163.185.148.245. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/