Ahmad Riza Ghazali

Multi‐dimensional non‐linear full waveform inversion of gas cloud reflection data using a genetic algorithm and a blended acquisition approach

In this paper, we present a multi-dimensional non-linear full waveform inversion approach using an optimized Genetic Algorithm (GA), which includes a blended acquisition approach to invert the highly non-linear gas cloud reflection response for its effective medium parameters. This non-linear inversion process is vital to construct full waveform transmission operators (including the codas) from the gas cloud reflection response via an effective medium representation. However, extending this approach to a 2D non-linear full waveform inversion is not simple or straightforward, as multi-parameter inversion may become inefficient. Furthermore, to simulate the actual seismic wavefield in the subsurface we use the finite difference method as the forward modeling process and thus it becomes an expensive inversion procedure for the GA. We demonstrate that multi-dimensional non-linear full waveform inversion to obtain effective gas cloud medium parameters from the gas reflection response is viable using a GA. Several modifications to the conventional GA are suggested to overcome its limitations and therefore to gain faster convergence of the inversion process.

2D Full Waveform Transmission Deconvolution For True Amplitude Imaging Below Gas-clouds

Summary Conventional imaging processes for a situation with a gas cloud do not offer satisfactory solutions. Due to the complex wave propagation through the anomaly and the transmission imprint on the reflections from below these complexities, the image below the anomaly is usually not properly recovered. We aim at constructing full waveform transmission operators (including the codas) from the gas cloud reflection response via an effective medium representation. True amplitude imaging is achieved via multi-dimensional deconvolution for these full waveform transmission operators. In this paper, we present a feasibility study on 2D synthetic data, for which the operators are obtained by forward modeling through the gas cloud region. For the 1.5D case, it is demonstrated that a target-oriented full waveform inversion process to obtain effective gas cloud for medium parameters is viable.

Seismic imaging through gas clouds: a data-driven imaging strategy

Summary In Malaysian Basins, offshore Malaysia, there are many imaging problems related to the so-called ’gas clouds’ or ’gas chimneys’. Conventional imaging processes do not offer satisfactory solutions, because of the complex propagation effects that occur. The involved simplified Green’s functions that are used in these algorithms do not properly describe the kinematics as well as the dynamic behavior of the actual visco-elastic wave propagation. The proposed method in this paper aims at solutions beyond the traditional imaging approaches. The focusing of the wavefield is addressed via the so called Common Focus Point (CFP) method. In this way an optimum focusing of the energy below the anomaly is obtained. Furthermore, the estimated migration operators can be translated into a velocity-depth background model by tomography inversion. A synthetic dataset with a complex, low velocity anomaly was generated. The CFP imaging approach has contributed significantly toward the improvement in reflector continuity and amplitude restoration. Finally, initial results on a field dataset confirm the viability of the approach.

An Innovative Approach to 3D Survey Design to Meet Exploration and Development Objectives - An OBC Case History from Offshore Malaysia

PETRONAS conducted a 3D-2C Ocean Bottom Cable (OBC) survey in the year 2012 offshore Malaysia, to appraise a recent hydrocarbon discovery and assist the field development plan and production enhancement initiatives. The legacy 3D towed streamer data acquired in 1984 suffered from poor imaging of the faults and significant navigation errors.

Shallow Gas Overburden Characterisation and Full Wavefield Modelling for Gas Clouds Imaging

Imaging complex subsurface like the gas clouds has always been challenging. Gas clouds are gas accumulation, trapped as an overburden that lowers P-wave velocities (Vp) and frequencies, disrupting transmitted energy and obscures events beneath it. Attenuation of seismic amplitude due to multiple scattering in thin layering of heterogeneous media was first reported by Anstey (1971). A nonlinear full waveform redatuming method proposed by Ghazali (2011) utilized multiple scattering phenomena which described the overburden as complex scattering and translated it to a transmission correction operator. Since it is a nonlinear full waveform inversion (FWI) method, it is important to characterize the rock properties in the gas clouds to identify factors that caused the formation of shallow overburden and help to constraint non-linear inversion results.