Obtaining seismic images of the subsurface near and beneath salt is very difficult due to seismic energy that is lost by propagating outside of the survey area or becoming evanescent at salt boundaries (poor illumination). We demonstrate an iterative regularized least-squares inversion for imaging that helps to compensate for illumination problems. We show the use of a regularization operator that acts to regularize amplitudes along reflection angles (or equivalent offset ray parameters) to compensate for the sudden, large amplitude changes caused by poor illumination. This regularization operator has the effect of filling in the gaps created in the reflection angle range due to the lost seismic energy. We demonstrate the use of this regularization operator in an iterative least-squares inversion scheme to improve imaging for a poorly illuminated 3-D seismic dataset.
He, Chuan (Department of Electrical Engineering) | Sun, Chuanwen (Department of Electrical Engineering) | Lu, Mi (Department of Electrical Engineering) | Zhao, Wei (Department of Computer Science, Texas A&M University, College Station, TX 77843)
A reconfigurable computing (RC) platform called SPACE (Seismic data Processing Accelerator with reConfigurable Engine) is proposed to accelerate the execution of 3D prestack Kirchhoff time migration (PSTM) based on the optimized 6
Coal mining that takes place underground is often done in the vicinity of poorly mapped and abandoned areas. These abandoned areas can contain water that has flooded into the old workings over time, as well as methane build-ups. Cutting into these areas poses a great risk to miners'' safety and can result in mine operation downtime. Costly drilling is often employed to locate these abandoned areas. Guided waves are very sensitive to seam perturbations and can be used to locate voids and faults within a coal seam. We recently acquired two in-seam seismic lines and have identified guided wave reflections that correlate with the location of the mine.
This paper is a continuation of the two presentations given at the University of Houston Forum (Dr. Han) and the University of Texas multicomponent Forum (Dr Tatham) in 2004. The thrust of the paper is to generate modeling and inversion examples to show the challenges of complex topology. Complex topology includes fractals. One tool to understand complex topology is inverse limit. Inverse limit uses an infinite sequence of simple objects to approximate a complex object and it is more general than recursive method.
Incorporating the shear component of multicomponent data has long held the promise of delineating sands from shales. Following the processing methodology outlined by Simmons (SEG 1999), 3D 9C shear wave data is sensitive to the difference in rigidity between sands, shales, and limestones. Two 3D 9 component seismic surveys were acquired to delineate Morrowan drill sites; one in SE Colorado, one in SW Kansas. Two 3D interpretations are presented which show a better than 80% match between 25 wells in eight square miles of 3D 9C seismic data. Twelve to eighteen foot thick sands can be detected. Sands less than six feet thick cannot be detected in these surveys. Shear wave data in both surveys show character anomalies not seen in the P wave data over the sands. An exploratory well was drilled in one of the surveys finding 30% more sand than any of the wells drilled pre-survey. 3D 9C data appears to be very robust in locating and delineating sands incised within a shale sequence.
Interpreting bright spots on amplitude stack data and/or of amplitude versus offset data (AVO) in terms of lithology, fluid, and porosity (LFP) may lead to ambiguous conclusions resulting in the of drilling of a dry hole. Rock physics-based forward modeling of seismic data presents an avenue to resolve this ambiguity by relating controlled perturbations in the underlying rock properties to diagnostic changes in seismic signal character.
The purpose of this work is to apply a geologic- and rock-physics-based forward-modeling methodology to a world-class gas reservoir, namely the AY-1 producing gas well of Ibhubesi Field, Orange River Basin. The forward-modeling process consists of five steps: (1) rock physics diagnostics and geologic interpretation of well and seismic data, (2) viable geologic model generation, (3) establishment of petrophysical transforms and population of the geologic models with realistic LFP values, (4) translation from rock properties to elastic properties, (5) synthetic seismogram generation and perturbation of the underlying rock properties to match the synthetic responses to the real seismic responses. Using well and seismic data from this sand-shale succession, we focus on the rock physics diagnostics, the geologic interpretation and seismic attribute analysis, and the statistical perturbation steps of the forward-modeling methodology. Seismic data provide the interpretation of the geologic setting supply information to predict reservoir properties away from well control.
Moro, Giancarlo Dal (University of Trieste) | Pipan, Michele (University of Trieste) | Forte, Emanuele (University of Trieste) | Burch, Donald N. (University of Trieste) | Finetti, Icilio (University of Trieste) | Forlin, Edy (University of Trieste) | Sugan, Monica (Apache Canada Ltd.)
We analyse and compare the shear-wave velocity distribution obtained from multi-fold SH reflection data and from Rayleigh wave dispersion curve inversion. The analysis focuses on two seismic datasets from a waste disposal site. We use an optimisation scheme based on a Genetic Algorithm and on the evaluation of the
Labat, Karine (Institut Français du Pétrole, France.) | Macé, Danièle (Institut Français du Pétrole, France.) | Bourgeois, Aline (Institut Français du Pétrole, France.) | Froidevaux, Pascal (Institut Français du Pétrole, France.) | Pichard, Morgane (Institut Français du Pétrole, France.) | Tonellot, Thierry (Institut Français du Pétrole, France.)