Abstract

Owing to the fact that the coal-beds are with the characteristics of multi-beds, thin single-bed, rapid lateral changes and deep burial, coal-bearing source rocks are difficult to be identified and predicted, especially in the lower exploration deepwater area. In this paper, a new integrative process utilizing geology and geophysics is proposed for better predicting the distribution of coal-bearing source rocks. Coal-beds were identified by the logging responses of “three higher, three lower, and one expand” and carbargilite were recognized by the characteristics of “four higher and one lower”. Based on the above logical decision, coal-beds and carbargilite can be distinguished automatically by cluster analysis of logging curves in verticality. Within the constraints of well-seismic calibration, the coal-beds group also can be detected in horizontality by the integrated representation of “negative phase, higher Q, lower impedance and lower frequency” within the seismic data. However, the distribution of coal-bearing source rocks utilizing geophysical methodology may do not conform to the geological rules of coal accumulation. And then the main geological controlling factors of coal accumulation are comprehensively analyzed as follows: (1) Paleotopography and tectonic subsidence determine the planar range of terrestrial-marine transitional facies markedly; (2) The relative sea level changes affect the accommodation space and shoreline migration, and limit the vertical range of coal-beds. More specifically, the relationship between the accommodation creation rate and the peat accumulation rate is a fundamental control on coal accumulation. The thickest and most widespread coals form where those two factors reached a state of balance; (3) The supply of autochthonous clasts and the distance between deposition places and paleovegetation accumulated area are the critical factor to form abundant coal, which means that if deposition area is close to paleouplift, there would be sufficient organic matters to form abundant source rocks. The results show that the integrated methods can significantly improve prediction accuracy of coal-bearing source rocks, which is suitable for early exploration of western deepwater area of South China Sea.

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