Jianchun Dai

Detection and estimation of gas hydrates using rock physics and seismic inversion Examples from the northern deepwater Gulf of Mexico

Natural gas hydrates, composed primarily of water and methane, are solid, crystalline, ice-like substances found in permafrost areas and deepwater basins around the world. As the search for oil and gas extends into ever-deeper waters, particularly within the northern Gulf of Mexico, gas hydrates are becoming more of a focus in terms of both safety and as a potential energy resource.

SITE SELECTION FOR DOE/JIP GAS HYDRATE DRILLING IN THE NORTHERN GULF OF MEXICO

Studies of geologic and geophysical data from the offshore of India have revealed two geologically distinct areas with inferred gas hydrate occurrences: the passive continental margins of the Indian Peninsula and along the Andaman convergent margin. The Indian National Gas Hydrate Program (NGHP) Expedition 01 was designed to study the occurrence of gas hydrate off the Indian Peninsula and along the Andaman convergent margin with special emphasis on understanding the geologic and geochemical controls on the occurrence of gas hydrate in these two diverse settings. NGHP Expedition 01 established the presence of gas hydrates in Krishna- Godavari, Mahanadi and Andaman basins. The expedition discovered one of the richest gas hydrate accumulations yet documented (Site 10 in the Krishna-Godavari Basin), documented the thickest and deepest gas hydrate stability zone yet known (Site 17 in Andaman Sea), and established the existence of a fully-developed gas hydrate system in the Mahanadi Basin (Site 19).

Seismic Reservoir Characterization In Marcellus Shale

The Middle Devonian Marcellus shale that extends from Ohio and West Virginia, northeast into Maryland, Pennsylvania and New York, is believed to hold in excess of a thousand trillion ft of natural gas. High-quality surface seismic data and top-of-the-line processing are essential to characterize these reservoirs and the overburden formations for safe and cost-effective drilling. A workflow comprising data acquisition and processing to prestack seismic inversion and lithofacies classification for characterizing the shale reservoirs is presented. The key elements in this workflow are dense point-receiver data acquisition and processing in the point-receiver domain. A small data set acquired with a proprietary point-receiver system was available to demonstrate the benefits of this methodology. The data were in an area in New York, where the Marcellus formation is known to exist.

Building a Seismic-driven 3D Geomechanical Model In a Deep Carbonate Reservoir

In this paper we show how to extend seismic-driven earth model building into the domain of geomechanics and drilling. A mechanical earth model (MEM) is a quantitative description of rock mechanical properties and in-situ stresses in the subsurface. Formation strength and in-situ stress are key components that impact well design. Most mechanical earth models, even today, are one-dimensional (1D), based on well and drilling data alone. The concept of using seismically derived horizons and velocities to extend the MEM into 3D space was introduced a few years ago. Very recently, a few authors have demonstrated the power of seismic inversion to improve the resolution and quality of a 3D MEM. We present a case-study from Kuwait (Sabriyah field) where a 3D geomechanical model was built using a combination of wellbore geomechanics, geologic structure, and seismic inversion-derived lithofacies and elastic properties. We show critical challenges facing seismic-based geomechanical model-building, demonstrate current solutions, and discuss future strategies.

Effective -stress-based reservoir characterization in an offshore basin

Summary Effective stress is a key attribute that enables the prediction of subsurface lithology units in overpressured basins. Because the seismic response of shales and sand depends on their compaction history, the effective stress will govern the sedimentary seismic response. This is in contrast to normally pressured regimes, where the depth below mudline (or overburden stress) is typically used to characterize the compaction effect. Effective stress enables one to map nonstationary sedimentary compaction in space. We use seismically derived effective stress as an additional attribute in the Bayesian Lithofacies classification (Bachrach et al., 2004; Mukerji et al., 2001). The other attributes in the process are elastic parameters such as acoustic and shear impedances and density obtained from the multiattribute seismic inversion (Roberts et al., 2005). The modified reservoir characterization method has been applied to a deepwater basin that contains reservoir units of the Pleistocene to the mid-Miocene age extending over a large area and is known to contain overpressure zones.

Rock Physics Models of Gas Hydrates and Their Implications in Seismic Detection

In this study, we use two gas hydrate wells in Canada to evaluate the existing rock physics models for gas hydrates and find the best-fit model for gas hydrate quantification using velocity information. The two wells have gas hydrate saturation estimates from resistivity and NMR data, respectively. We use the gas hydrate saturation estimates and model the P- and S-wave velocity responses using several existing rock physical models. The estimated velocities were then compared with the measured velocities from the well. The result indicates that the effective medium theory model which treats gas hydrates as load-bearing grains matches the well log data best. We apply this model to a 3D seismic volume in the deepwater Gulf of Mexico (GOM) and predict gas hydrate concentration using seismic inversion techniques.

Reservoir Property Estimation in Carbonates

We present some key challenges in rock and fluid property prediction in carbonates. Most traditional rock physics models have been developed for siliciclastic rocks. Carbonates, which have a completely different mineralogy, pore structure and geometry, pose new challenges to us. We look into the applicability of traditional rock physics models on carbonate reservoirs. We analyze the effect of porosity, mineralogy, clay content, and fluids on the bulk and shear stiffness of carbonate rocks in a middle-eastern deep reservoir, composed predominantly of limestone with varying proportions of anhydrite, dolomite, and clay. We also analyze the effect of in-situ stresses on the elastic properties, with particular emphasis on pore-pressure. We demonstrate the ability to model the elastic properties (bulk and shear moduli) as functions of mineralogy, clay content, porosity, and pore-pressure. We use a stochastic rock physics framework to build a probabilistic forward model, based on and calibrated to well-log and drilling data. Using the joint probability distribution functions, we use a Bayesian inversion technique to estimate reservoir properties (porosity, clay content, and pore-pressure) from seismic inversion data (acoustic impedance, shear impedance, and density) along with the associated uncertainties.

Converted-wave elastic impedance inversion in practice: A case study in the Gulf of Mexico

The 2D line under study is one in a multiline grid of a largescale, 2D-4C OBC, long-offset (up to 10,000 m) acquisition program that covers a large number of OCS blocks in the northern Gulf of Mexico. Figures 1 and 2 show the PP and PS image of this line, with a gamma ray log overlaying on the sections. We see that seismic imaging near the target zone has been hampered by a severe gas cloud effect in the PP data, while the PS data have much better quality in and below the gas cloud. In the prestack domain, the signal-to-noise ratio (SNR) of the PS gathers near the reservoir is also much higher than the SNR of the PP gathers (not shown here due to space limitation).