Oil Size Distribution Research Articles

Experimental Investigation of Oil Droplet Size Distribution in Underwater Oil and Oil-Air Jet

Abstract Understanding the droplet size distribution of subsea oil releasing is important to predict the subsequent transport and degradation of the spilled oil. Single- and multi-phase oil jet experiments were conducted in the Ohmsett facility, including pure oil jet and oil-air jet through a 10.7-mm pipe and a 4.7-mm pipe. Measurements of the vertical jet hydrodynamics and the oil size distribution were obtained. The reported results help to extend subsea oil spills experiment scale into a meso-scale, and the measurement range of the oil size is widened up to 2 cm. Moreover, the application of dispersant and involvement of air phase provided valuable scientific evidence for the usage of dispersants to treat oil spills. The data confirmed the effectiveness of the dispersant that reduces oil droplet size and also suggested that the participation of the gas phase facilitated the decreasing of oil droplet size. The results were compared to the numerical simulation tool VDROP-J. While the hydrodynamics showed good consistency, the system-dependent coefficient needed a slight revision to coincide with presented data. This also confirmed the significance of experimental materials for further validation and development of oil spill models, where we also provided guidance and discussion on conducting and post-processing the oil spill experiment.

Size distribution and dynamics of oil and gas field discoveries in petroleum basins

The size distribution of oil and gas fields within an arbitrary petroleum basin is approximated by the truncated Pareto distribution. We propose definite expressions for assessing the number and total resources of fields having any preset limits of field sizes and describe the application of simulational mathematical modeling for assessing the resource structure of a petroleum basin. The exploration filter model, which is a formal expression of oil and gas exploration strategy, is proposed. A definite expression for the filter operating in a given basin can be obtained from the history of oil and gas discoveries in that basin. The proposed concept can be used to predict the sequence of oil and gas fields of various sizes that are likely to be discovered in the basin during further exploration.

Application of the modified Arps-Roberts discovery proces model to the 1995 U.S. National Oil and Gas Assessment

ARDS (version 4.01), a modified version of the Arps-Roberts discovery process model, was used to forecast the remaining oil and gas resources in more than 50 provinces, super-exploration plays, and individual plays in the onshore and offshore United States for the 1995 National Oil and Gas Assessment. The size distribution of oil and gas fields was estimated for the underlying distribution of fields; the size distribution for the remaining fields was calculated to be the difference between this distribution and that of discovered fields. The guidelines that govern the 1995 National Assessment require the underlying size distribution of fields to be estimated by using only data from two standard commercial data files (the NRG Associates field file and the Petroleum Information Inc. well file). However, a variety of situations required further modification of the discovery process modeling system; for example, multiple exploration plays that occurred nearly simultaneously and also displaced each other in time, and the phenomenon of field growth introduced a large bias in the forecasts produced by the discovery process models for some provinces.

Lognormality in the observed size distribution of oil and gas pools as a consequence of sampling bias

Economic filtration has been offered as an explanation of the observed lognormality in the size distribution of discovered oil and gas deposits. The result leads to the conclusion that one cannot impute the shape of the underlying parent distribution from the observed discoveries size distribution. The fact that the largest pools tend to be discovered early in the exploration history of an area of interest suggests the existence of an inherent sampling bias in the discovery process. The bias is influenced by the levels of geologic knowledge and technological sophistication. Furthermore, the existence of the bias leads to lognormality in the observed discoveries size distribution of oil and gas pools. A discovery process model explicitly incorporating the notion of sampling bias was applied to a series of Weibull parent frequency size distributions. The selected parent distributions are of a class suggested in the literature as more reflective of nature's size distribution and have empirical support. The distribution of discoveries resulting from the application of the model to the chosen parent size distributions were tested for lognormality using a chi-squared test. Lognormality was found to be an acceptable model of the discoveries size distribution over a wide range of resource exhaustion measures. When combined with the notion of economic filtration, sampling bias leads to the conclusion that one should not expect the lognormal distribution to accurately represent the underlying parent size distribution of oil and gas deposits.

A three-dimensional model to predict future oil discoveries in spatially connected multiple plays

A discovery-process model that had been devised previously to estimate the size distribution of oil and gas fields remaining to be discovered in a single producing horizon was adapted to a basin containing spatially connected multiple plays and producing horizons. This model used the concept of the area of influence of wells to estimate search effort. Other variables estimated from the historical drilling and discovery data are the effective basin size and the exploration-drilling efficiency. Data from the Midland Basin are used to illustrate how the model works.