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However, these methods tend to focus on the distinction between biogenic and thermogenic gas. The natural thermal evolution of and hydrocarbon generation from organic matter in open, semi-open, and closed systems have been simulated in numerous experiments (Schenk and Horsfield, 1993; Behar et al., 1995; Tang and Behar, 1995; Lewan and Ruble, 2002). The organic material in coal is relatively aggregated and exhibits high sorption ability, which led Hill et al. (2003) to argue that coal is typically generated in closed or semiclosed systems. Generally, hydrous pyrolysis experiments can only be conducted in closed systems (Lewan et al., 1979; Lewan, 1985). Meanwhile, considering the vitrinite reflectance of pyrolyzed kerogens change in a manner similar to that observed in the natural system, the relationship between hydrocarbon yield and temperature obtained from hydrous pyrolysis experiments in closed systems can be applied practically (Lewan and Williams, 1987). The present study aims to understand the geochemical characteristics of CBM and identify its source (i.e.,

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Although joint migration inversion has been proposed for several years, a thorough derivation and description of the involved gradients was not published. In this paper, we derive the gradient of both the angle‐independent reflectivity and the velocity in a framework of acoustic angle‐independent joint migration inversion. With some further approximations taken, the conclusions shown in previous publications can also be reached from our new derivation.

The method of exploration seismics aims at creating an image of the earth's subsurface structures by active acoustic reflection measurements. However, seismic images acquired from land data are often severely degraded due to complex propagation effects near the surface of the earth. Although some methods have been proposed to address the near-surface problem, it remains largely unsolved. We propose a solution that involves an estimation of the true wave propagation effects through the near-surface area in order to compensate for them without explicitly estimating a velocity-depth model. The estimated oneway propagation operators describe wave propagation between the surface level (i.e., the acquisition level) and a laterally consistent datum reflector level. They are parameterized by oneway travel times along a predefined lateral grid. Based on this solution we present a self-adjustable input genetic algorithm (SAIGA) to estimate these travel time functions. SAIGA is an advanced and scalable genetic algorithm that can overcome the hurdle of excessive calculation time due to large 3-D data volumes, as it optimizes the parameters on a representative subset that is randomly selected and periodically updated from the full input dataset. Finally, we apply SAIGA to a 3-D field dataset containing 2.4 million traces yielding good results within a reasonable calculation time.