QUANTITATIVE ESTIMATES OF OIL LOSSES DURING MIGRATION, PART I: THE SATURATION OF PATHWAYS IN CARRIER BEDS

X. R. Luo1*, B. Zhou2, S. X. Zhao3, F. Q. Zhang2 and G.Vasseur4

1 Key Laboratory of Petroleum Resource Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China.

2 Exploration & Production Research Institute, SINOPEC, Beijing, 100083, China.

3 Institute of Crustal Dynamics,China Seismological Bureau,Bejiing 100085,China.

4 SISYPHE, UMR7619, Boîte 123, Université Paris VI, 75252 Paris Cedex 05, France.

*Author for correspondence, email: luoxr@mail.iggcas.ac.cn

Estimates of hydrocarbon losses during migration are critical to petroleum resource assessments based on mass balance calculations. Using knowledge acquired from physical experiments, we conducted numerical experiments to qualitatively simulate migration processes on a basin scale, and we have estimated the proportions of oil lost along different parts of the migration pathway. Between the point where oil is expelled from a source rock and its arrival in a trap, migration pathways were divided into three sections, namely vertical and lateral pathways within the area of the effective source rock (W1), and lateral pathways outside this area (W2).

With reference to the concept of an independent migration unit (IMU), a prism-shaped domain with square top and bottom faces, the proportion of vertical pathways (Q1) and lateral pathways (Q2) in carrier beds in W1 may be estimated, using parameters obtained in migration experiments. The proportion of oil lost in W2 was obtained by statistical analysis of modelled results. It is found that the loss of oil within W2 decreases rapidly with increasing distance from the contact between W1 and W2.

Relative oil losses in migration pathways were estimated by considering two typical migration models: a sloping rectangular plate model, and a circular synclinal model. Simulation results show that, for sandstone carrier beds at a basin scale, Q2 is one order of magnitude less than Q1, and losses (Q3) in W2 are two orders of magnitude less than those (Q1+ Q2) in W1.

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