基于ASTER和模糊逻辑的卫星油气勘探

IF 2.6 Q3 ENERGY & FUELS
Reza Taheri PhD , Alan Merville Tait PhD
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引用次数: 2

摘要

尽管已知遥感在广泛的工业和情况中有实际应用,但它尚未广泛用于石油勘探,石油勘探主要依靠地质和/或地球物理调查。自先进星载热发射与反射辐射计(ASTER)投入使用以来,随着传感设备的进步,在石油勘探背景下,需要对地表发射率、地表动力学温度、亮度温度和地表辐射等潜在指标的提取进行重新评估。利用与地热活动相关的地表温度(LST)异常来确定是否有石油存在,ASTER可以在地表探测到热异常。研究区位于伊朗陆上,由53个现有的富油区组成。覆盖研究区域的20幅ASTER场景(颗粒)由美国国家航天局(NASA)提供。为了突出地表探测到的地热异常的地下因素,假定是由下伏碳氢化合物引起的,对ASTER图像进行了处理,以尽量减少由下伏碳氢化合物以外的任何来源引起的温度变化。为了根据角色扮演变量对最终LST的影响程度来分配权重,采用模糊逻辑作为主要的处理方法。在处理后的图中,在去除所有影响地表温度的因素后,剩余的热异常(在研究区域的某些地区减少了80%)可以与下面的碳氢化合物联系起来。最终结果表明,即使在排除所有地表温度影响因素的影响后,研究区油藏缓冲带内67.9%(53个含油区中的36个)的像元仍被认为是热异常的。利用变异图分析了各储层缓冲带内不同方向上热异常的连续性。变异函数分析结果表明,即使研究区部分储层缓冲带内探测到的热异常不高,但热异常方向强烈遵循NW-SE方向,即沿油藏延伸轴趋势线方向。详细的空间分析后的LST处理将报告。利用地理信息系统和模糊逻辑,建立了一个动态模型,该模型可以根据目标地区的热规格和特征进行定制和更改。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Satellite-based hydrocarbon exploration employing ASTER and fuzzy logic

Despite the known practical applications of remote sensing in a wide range of industries and situations, it has not been used extensively in petroleum exploration, which has relied mostly on geological and / or geophysical surveys. With the advances made in sensing equipment since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) became operational, extraction of potential indicators such as: surface emissivity, surface kinetic temperature, brightness temperature and surface radiance need to be re-evaluated in the context of petroleum exploration.

Land Surface Temperature (LST) anomalies associated with geothermal activity was used, to determine if petroleum in place, can be the source of thermal anomalies detected at surface, by ASTER. A study area, in onshore Iran, consisting of 53 existing petroleum-rich areas was selected. Twenty (20) ASTER scenes (Granules) covering the study area were provided by National American Space Agency (NASA).

In order to highlight subsurface contributors to geothermal anomalies detected at surface, assumed to be due to underlying hydrocarbons, ASTER images were processed to minimize temperature variations caused by any sources other than the underlying hydrocarbons. In order to assign weight to the role-playing variables according to their degree of influence over the final LST, fuzzy logic was employed, as the main processing approach. In the resulting processed maps, following the removal of all the contributors to LST, the remaining thermal anomalies, which were reduced up to 80% in some areas of the study area, could then be linked to the underlying hydrocarbons. The final results indicate that, even after the influence of all the contributors to LST has been removed, still 67.9% (36 out of 53 petroleum containing areas) of the pixels within the buffer zones of petroleum reservoirs of the study area are considered to be thermally-anomalous.

Continuity of thermal anomalies, in different directions, was also investigated within the buffer zones of each of the petroleum reservoirs, by Variograms. The results of the Variogram analysis indicate that even if the detected thermal anomalies within the buffer zones of some of the reservoir of the study area were not high, the direction of thermal anomalies strongly follow the NW-SE direction, which is the direction along the trend line of elongation axes of petroleum reservoirs. Details of the spatial analysis post LST processing will be reported.

By employing GIS and fuzzy logic, a dynamic model was developed, with variable input data from geology and ASTER, which could be customised and changed according to target area's thermal specifications and characteristics.

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