Search

Novel/Additive Information: The paper presents a simple and computational fast method to predict CO2 injectivity and well pressure as a function of time. The application of superposition in time - a method usually associated with solving linear problems - is demonstrated to adequately solve the complex non-linear problem of CO2 injectivity. Because the method includes material balance, it can help to define storage efficiency factors.

Up-down deconvolution remains a powerful tool for the processing of ocean-bottom node data through its ability to efficiently attenuate free-surface multiples along with the source ghost and signature. Practical receiver-domain implementations in the frequency-wavenumber domain, however, assume layer-cake geology and can leave residual multiples from dipping multiple generators. Using synthetic and real data examples, we examine the layer-cake limitations of receiver-domain up-down deconvolution and propose the use of a wave-equation deconvolution residual demultiple approach. In contrast to many multiple attenuation approaches, the proposed flow does not require any adaptive subtraction for either the up-down deconvolution or the wave-equation deconvolution demultiple steps.

In this paper we will focus on the resolution of the strong imaging challenges of the area. First, we will show how the combination of Multi Wave Inversion (MWI), joint First Break (FB) and slope tomography, and Full Waveform Inversion enabled to construct a high resolution near surface velocity model which solved the important distortions caused by the varied terrain and rough topography. Then we will give insight on an advanced Multi Layer Tomography workflow complemented by TL Full Waveform inversion. It enabled to finely capture the strong lateral and vertical velocity contrasts of large thrust, thus enabling to restore the focusing and faulted structure of the Jurassic reservoir units underneath

Time series are analysed to detect changes and predict future behaviour. Monitoring of the surface or subsurface in Geoscience provides such time series. As new data becomes available, changes of regime are detected. They should be identified as early as possible with as few false positive as possible. In this paper, we define the ideas of regime and change of regime in a time series. We then give an overview of the Bayesian method used to detect these changes. The principles are illustrated with an application for the detection of a mine tailings dam failure using InSAR satellite data.

2D deconvolution is an attractive approach for short period multiple prediction as it does not require direct recording of the multiple generator and can model multiples relating to more than one multiple generator at a time. One drawback, however, relates to an inherent over prediction of mixed side multiples leading to an inconsistency in the amplitude of multiple predictions from one multiple order to the next. We present a modified form of predictive deconvolution that iteratively refines the prediction operator and prevents the over prediction of higher order multiples. The resulting multiple prediction is consistent with the amplitude of multiples in the recorded data, reducing the necessity for adaptive subtraction. The algorithm may be applied in 2D or 3D, or alternatively with a receiver only side 3D implementation suited to towed streamer geometries. The effectiveness of the algorithm is demonstrated on synthetic data as well as on two towed streamer 3D seismic data examples acquired in the North Sea.

Solving fault shadow imaging problems has been a long-existing topic when heavy faults are present and the seismic imaging underneath is distorted. With full-waveform inversion (FWI), they are usually less of a concern when their depths are within diving wave penetration. However, beyond diving wave penetration, we have to rely on reflection energy, either by various tomographic methods or reflection FWI, both of which require special considerations in order to effectively resolve small-scale velocity anomalies associated with faults. In this paper, we present applications of fault-constrained tomography (FCT) and Time-lag FWI (TLFWI) with a weighted tomographic term for deep fault imaging using a streamer dataset with limited offsets from the South China Sea. Our learnings show FCT heavily hinges on high-quality common image gather (CIG) and fault picking. With a weighting factor to promote the tomographic term from reflection energies, the TLFWI workflow successfully corrected fault shadows and demonstrated advantages over FCT for resolving velocity anomalies in areas of complex faults.

We present the main results of a tailored velocity model building workflow on a recent broadband survey from North Kuwait. Depth imaging in Kuwait presents several challenges, including the need to capture the strong velocity variations of a complex near surface that generates long and short wavelength distortions, the need for a detailed velocity model to accurately restore the structures of low-relief and faulted Cretaceous and Jurassic traps, and the difficult imaging of the Paleozoic structure hidden below a curtain of multiples. First, we give insight on a Multi-Wave Inversion and Full-Waveform Inversion workflow, which exploited the finely sampled surface waves and the diving waves to derive a high-resolution near-surface P-wave velocity model. Then we show how high-definition Multi-Layer Tomography is able to capture the complex velocity variations within the Cretaceous, which helps resolve imaging distortions. Finally, we focus on the imaging of the Paleozoic structures, which are key to understanding the regional geological history.

Applications of full-waveform inversion (FWI) to land data have proven much more challenging than to marine data. The difficulties are linked to a lower signal-to-noise ratio but also to a greater influ-ence of elastic wave phenomena in these data sets, especially those characterized by strong elastic property contrasts. The Middle East, where FWI-dedicated acquisitions and pre-processing work-flows have been developed, has emerged as a promising proving ground for land acoustic FWI. But it also proved to be challenging due to strong elastic effects from alternating fast and slow velocity layers in the shallow section. Elastic land FWI then appears as a natural solution to be investigated, especially considering that it becomes more practical thanks to the progresses of the computing ca-pacities. We study the potential of elastic land FWI to overcome the limitations of acoustic land FWI, through a set of synthetic and real data applications to typical challenging areas from the Mid-dle East. We show the improved data fitting leading to an increased resolution and stability that can be obtained with elastic land FWI compared to acoustic land FWI when inverting diving waves. We also present some preliminary inversion results of ultra-low frequency surface-waves obtained by interferometry.

Fizz gas detection is a critical step in field development as it is often difficult to differentiate it from commercial gas in reservoirs on acquired seismic data. In a shallow reservoir context, it is theoretically possible to observe a fizz gas effect through a joint analysis of P-wave velocity (Vp) and density (Rhob) properties. Although inverting density is routinely done in pre-stack inversion, it is generally too strongly coupled to Vp to achieve an efficient fizz gas characterization through a Vp versus Rhob crossplot. This paper presents a pre-stack inversion case study conducted in offshore North Sabah, Malaysia, to characterize Late and Middle Miocene clastic, gas-bearing deposits. Very high-quality pre-stack seismic data allowed for the possibility to partially decouple Vp and density through an adequate inversion parameterization. Supported by fluid change predictions coming from a petro-elastic model calibrated to the field conditions, a fizz gas characterization routine could be established through a joint analysis of the inverted Vp and Rhob properties, giving access to a potential fizz gas detection over the targeted reservoir.