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**Summary**

We developed an elastic full waveform inversion method for determining microseismic event location and source focal mechanism simultaneously. With given P- and Svelocity models, the method inverts three component data and iteratively updates event location and source moment tensor solutions. Unlike inverting seismic data from controlled sources, we must infer origin time of microseismic events during inversion in order to match waveform properly. This is solved by calculating cross correlation of the input and synthetic waveform envelopes and extracting time shifts during each inversion iteration. Because the values of location and moment tensor parameters are not in the same order, we apply a scaling factor to adjust the updates so that they both can be resolved. Numerical experiments and real data applications suggest that fitting full waveform data leads to reliable solutions.

derivative, displacement, elastic full waveform inversion, event location, example 1, full waveform inversion, information, initial location, inversion, microseismic data, Reservoir Characterization, source location, source mechanism, tensor, true model, Upstream Oil & Gas, velocity model, waveform, Waveform Inversion, waveform overlay

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

ABSTRACT Micro-seismic event estimation results depend highly on the velocity accuracy. Full waveform inversion (FWI) has been employed to invert for the velocity and micro-seismic source image, simultaneously. However, conventional FWI suffers from the infamous cycle-skipping problem, which is even more serious when the source location is unknown. To mitigate this issue, we formulate an optimization problem to linearly reconstruct the wavefield in an efficient matter using the background model information and allow an enhanced source function to absorb the secondary (perturbation) source information. This reconstructed wavefield is then used to update this enhanced source function using the same background wave equation modeling operator without any inversion or update process. We then use the reconstructed wavefield to extract from the enhanced source function the parts corresponding to the micro-seismic source image and those corresponding to secondary sources (velocity perturbations), which can be used to update the model. In the outer loop iterations we repeat the processes of inverting for the source and updating the model until we achieve convergence. This process and its effectiveness is demonstrated on a complicated synthetic model and a field dataset. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 9:20 AM Presentation Start Time: 11:25 AM Location: Poster Station 3 Presentation Type: Poster

SEG-2019-3215179

Alkhalifah, Artificial Intelligence, efficient wavefield inversion method, hydraulic fracturing, inversion, inverted source image, iteration, Marmousi model, micro-seismic event estimation, optimization problem, perturbation, Reservoir Characterization, seg international exposition, source function, source image, source location, true source location, Upstream Oil & Gas, velocity model, Wave Equation, wavefield

SPE Disciplines:

Technology: Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (0.35)

In the microseismic field, a complete characterization of events involves determining the positioning and focal mechanism properties, which requires an accurate seismic velocity model. Conversely, the construction of a velocity model with surface seismic data suffers from a lack of full illumination, a deficit which could in principle be mitigated by microseismic event ray paths. The velocity model and event characterization problems are in this sense strongly interconnected, each, if it were solved, supporting the other. Assuming an imperfect velocity model derived from surface seismic data as a starting point, and microseismic events as data, a full waveform inversion (FWI) methodology involving simultaneous updates in both source property model parameters and velocity model parameters can be formulated. The resulting gradient and Hessian quantities can be used to solve the inverse problem for all unknowns, or, equally importantly, to help quantify the cross-talk between velocity and source models, optimize acquisition, and act as a tool for appraisal. In this paper we formulate a basic scalar acoustic version of microseismic full waveform inversion (MFWI), set out the forms for the gradients, present an early-stage numerical analysis of MFWI updates, and comment on some important aspects of cross-talk between velocity model and source properties.

Presentation Date: Monday, October 15, 2018

Start Time: 1:50:00 PM

Location: 207C (Anaheim Convention Center)

Presentation Type: Oral

crosstalk, full waveform inversion, full-waveform inversion, geometry, gradient, Implementation, information, inversion, iteration, microseismic event, Reservoir Characterization, seg international exposition, source location, source position, source term gradient, source-term gradient, true source location, Upstream Oil & Gas, velocity model, velocity model term, Waveform Inversion

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

To compute the spatial and temporal location of a microearthquake, we have extended the theory of wave-equation traveltime inversion (WTI). WTI takes full advantage of modern techniques in forward modeling. Thus, source parameters can be inverted under complicated velocity structures, with strong anisotropy and lateral heterogeneities.

For global location of events, the adjoint-state method computes the gradients of the objective function. This method requires a single modeling to calculate the gradients of all source parameters. Against synthetic data with strong random noises, this algorithm achieves decent location results.

We also extend WTI for relative location of events, which we further extend to a form that does not depend on model. This algorithm is applied to a field microseismic dataset monitored by the surface patch receivers, from which the Jacobian matrices of the traveltime are extracted directly. The results achieve excellent agreements with the event locations obtained from an optimized velocity model.

Presentation Date: Monday, October 17, 2016

Start Time: 4:35:00 PM

Location: 144/145

Presentation Type: ORAL

adjoint-state method, algorithm, Artificial Intelligence, derivative, event location, forward modeling, geometry, gradient, inversion, microseismic event location, objective function, optimization problem, receiver, relative location, Reservoir Characterization, seg seg international exposition, seismogram, source parameter, Upstream Oil & Gas, velocity model, wave-equation traveltime inversion

SPE Disciplines: Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)

Technology: Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (0.37)

Waveform inversion (WI), which has been extensively used in reflection seismology, could provide improved velocity models and event locations for microseismic surveys. Here we present an elastic, anisotropic WI algorithm for microseismic data designed to estimate the 3D velocity field along with the source locations. The gradient of the objective function with respect to the source and medium parameters is obtained using the adjoint-state method, with only two modeling simulations performed at each iteration. In the current implementation for VTI (transversely isotropic with a vertical symmetry axis) models, the source coordinates and velocity parameters are estimated sequentially at each stage of the inversion to minimize trade-offs and improve the convergence. Synthetic examples illustrate the performance of the algorithm for a 3D cloud of dislocation sources embedded in a layered VTI medium.

Presentation Date: Monday, September 25, 2017

Start Time: 1:50 PM

Location: 360D

Presentation Type: ORAL

algorithm, annual meeting, Artificial Intelligence, event location, hydraulic fracturing, inversion, iterative microseismic event location, jarillo michel, layered vti medium, microseismic data, Modeling & Simulation, objective function, optimization problem, Reservoir Characterization, seg seg international exposition, sequential inversion, Source coordinate, Tsvankin, Upstream Oil & Gas, velocity analysis, velocity model, velocity parameter, vti velocity analysis, Waveform Inversion

SPE Disciplines:

Technology:

Thank you!