摘要:
A computer-implemented method for updating a physical properties model of a subsurface region in an iterative inversion of seismic data using a gradient of a cost function that compares the seismic data to model-simulated data, said method comprising: obtaining a contrast model of a subsurface physical parameter that is sensitive to data dynamics and a kinematic model of a subsurface physical parameter; determining a gradient of a cost function using the contrast model and the kinematic model, wherein the cost function compares seismic data to model-simulated data; updating the kinematic model using a search direction derived from the gradient; adapting the contrast model according to an update to the kinematic model performed in the updating step; iteratively repeating the determining, updating, and adapting steps until a predetermined stopping criteria is reached, and generating a subsurface image from a finally updated kinematic model; and using the subsurface image to prospect for hydrocarbons.
摘要:
A computer-implemented method for updating subsurface models including: using an offset continuation approach to update the model, and at each stage defining a new objective function where a maximum offset for each stage is set, wherein the approach includes, performing a first stage iterative full wavefield inversion with near offset data, as the maximum offset, to obtain velocity and density or impedance models, performing subsequent stages of iterative full wavefield inversion, each generating updated models, relative to a previous stage, wherein the subsequent stages include incrementally expanding the maximum offset until ending at a full offset, wherein a last of the stages yields finally updated models, the subsequent stages use the updated models as starting models, and the full wavefield inversions include constraining scales of the velocity model updates at each stage of inversion as a function of velocity resolution; and using the finally updated models to prospect for hydrocarbons.
摘要:
A computer-implemented method for updating a physical properties model of a subsurface region in an iterative inversion of seismic data using a gradient of a cost function that compares the seismic data to model-simulated data, said method comprising: obtaining a contrast model of a subsurface physical parameter that is sensitive to data dynamics and a kinematic model of a subsurface physical parameter; determining a gradient of a cost function using the contrast model and the kinematic model, wherein the cost function compares seismic data to model-simulated data; updating the kinematic model using a search direction derived from the gradient; adapting the contrast model according to an update to the kinematic model performed in the updating step; iteratively repeating the determining, updating, and adapting steps until a predetermined stopping criteria is reached, and generating a subsurface image from a finally updated kinematic model; and using the subsurface image to prospect for hydrocarbons.
摘要:
A computer-implemented method for updating subsurface models including: using an offset continuation approach to update the model, and at each stage defining a new objective function where a maximum offset for each stage is set, wherein the approach includes, performing a first stage iterative full wavefield inversion with near offset data, as the maximum offset, to obtain velocity and density or impedance models, performing subsequent stages of iterative full wavefield inversion, each generating updated models, relative to a previous stage, wherein the subsequent stages include incrementally expanding the maximum offset until ending at a full offset, wherein a last of the stages yields finally updated models, the subsequent stages use the updated models as starting models, and the full wavefield inversions include constraining scales of the velocity model updates at each stage of inversion as a function of velocity resolution; and using the finally updated models to prospect for hydrocarbons.
摘要:
Method for reducing computational time in inversion of geophysical data to infer a physical property model (91), especially advantageous in full wavefield inversion of seismic data. An approximate Hessian is pre-calculated by computing the product of the exact Hessian and a sampling vector composed of isolated point diffractors (82), and the approximate Hessian is stored in computer hard disk or memory (83). The approximate Hessian is then retrieved when needed (99) for computing its product with the gradient (93) of an objective function or other vector. Since the approximate Hessian is very sparse (diagonally dominant), its product with a vector may therefore be approximated very efficiently with good accuracy. Once the approximate Hessian is computed and stored, computing its product with a vector requires no simulator calls (wavefield propagations) at all. The pre-calculated approximate Hessian can also be reused in the subsequent steps whenever necessary.
摘要:
Method for reducing computational time in inversion of geophysical data to infer a physical property model (91), especially advantageous in full wavefield inversion of seismic data. An approximate Hessian is pre-calculated by computing the product of the exact Hessian and a sampling vector composed of isolated point diffractors (82), and the approximate Hessian is stored in computer hard disk or memory (83). The approximate Hessian is then retrieved when needed (99) for computing its product with the gradient (93) of an objective function or other vector. Since the approximate Hessian is very sparse (diagonally dominant), its product with a vector may therefore be approximated very efficiently with good accuracy. Once the approximate Hessian is computed and stored, computing its product with a vector requires no simulator calls (wavefield propagations) at all. The pre-calculated approximate Hessian can also be reused in the subsequent steps whenever necessary.
摘要:
A basically time-domain method for performing full wavefield inversion of seismic data to infer a subsurface physical property model (61), where however at least one quantity required for the inversion, such as the Hessian of the cost function, is computed in the frequency domain (64). The frequency-domain quantity or quantities may be obtained at only a few discrete frequencies (62), preferably low frequencies, and may be computed on a coarse spatial grid, thus saving computing time with minimal loss in accuracy. For example, the simulations of predicted data and the broadband gradient of the objective function may be computed in the time domain (67), and the Hessian matrix, approximated by its diagonal, may be computed in the frequency domain. It may be preferable to use time-domain and the frequency-domain solvers that employ different numerical schemes, such as finite-difference method, one-way wave equation, finite-element method (63).
摘要:
Method for improving convergence in gradient-based iterative inversion of seismic data (101), especially advantageous for full wavefield inversion. The method comprises decomposing the gradient into two (or more) components (103), typically the migration component and the tomographic component, then weighting the components to compensate for unequal frequency content in the data (104), then recombining the weighted components (105), and using the recombined gradient to update (106) the physical properties model (102).
摘要:
Method for estimating the Hessian of the objective function, times a vector, in order to compute an update in an iterative optimization solution to a partial differential equation such as the wave equation, used for example in full wave field inversion of seismic data. The Hessian times vector operation is approximated as one forward wave propagation (24) and one gradient computation (25) in a modified subsurface model (23). The modified subsurface model may be a linear combination of the current subsurface model (20) and the vector (21) to be multiplied by the Hessian matrix. The forward-modeled data from the modified model are treated as a field measurement in the data residual of the objective function for the gradient computation in the modified model. In model parameter estimation by iterative inversion of geophysical data, the vector in the first iteration may be the gradient of the objective function.
摘要:
Embodiments use seismic processing methods that account for the spatial variability of surface wave velocities. Embodiments analyze surface wave properties by rapidly characterizing spatial variability of the surface waves in the seismic survey data (302). Filtering criteria are formed using the spatial variability of the surface waves (204). The filtering criteria can then be used to remove at least a portion of the surface waves from the seismic data (206, 319). The rapid characterization involves estimating a local group velocity of the surface waves by cross-correlation of the analytic signals (302).