CAJ | 학술논문

回剥分析(backstripping)是盆地沉降史分析的核心方法，应用极为广泛；但对其分析结果的不确定性及参数对分析结果的影响的关注甚少。以珠江口盆地白云凹陷地区为例，探讨了原始数据和选用参数(包括无钻井揭示的基底埋深和界面年龄、地层划分、孔隙度随深度变化曲线、沉积岩性、古水深和全球海平面变化等)对回剥分析结果的影响。理论分析和灵敏度试验表明，无钻井揭示的基底埋深的误差影响回剥分析的所有结果；界面年龄的误差仅影响对沉积速率和构造沉降速率的估计；岩性的影响反映在选取密度和孔隙度随深度变化的曲线参数之中，孔隙度在不同地区可能有较大差异；而古水深是回剥分析参数中不确定性最大的因素，古水深的误差不影响去压实厚度和沉积速率，但却100%成为构造沉降量的误差。由于陆坡区古水深和岩性随位置的变化较大，这两种参数对陆坡区回剥分析结果的影响尤为显著，需要采用随位置而变的参数，特别需要综合利用各种地质地球物理资料估计各地层沉积时的古水深变化。数据的不确定性及参数选取的不当有可能导致谬误的结果，因此发表回剥分析结果时应该说明主要参数的选取依据，而对于文献中发表的回剥分析结果则必须在考察其数据和参数的不确定性后才能考虑采用与否。
회박분석(backstripping)시분지침강사분석적핵심방법，응용겁위엄범；단대기분석결과적불학정성급삼수대분석결과적영향적관주심소。이주강구분지백운요함지구위례，탐토료원시수거화선용삼수(포괄무찬정게시적기저매심화계면년령、지층화분、공극도수심도변화곡선、침적암성、고수심화전구해평면변화등)대회박분석결과적영향。이론분석화령민도시험표명，무찬정게시적기저매심적오차영향회박분석적소유결과；계면년령적오차부영향대침적속솔화구조침강속솔적고계；암성적영향반영재선취밀도화공극도수심도변화적곡선삼수지중，공극도재불동지구가능유교대차이；이고수심시회박분석삼수중불학정성최대적인소，고수심적오차불영향거압실후도화침적속솔，단각100%성위구조침강량적오차。유우륙파구고수심화암성수위치적변화교대，저량충삼수대륙파구회박분석결과적영향우위현저，수요채용수위치이변적삼수，특별수요종합이용각충지질지구물리자료고계각지층침적시적고수심변화。수거적불학정성급삼수선취적불당유가능도치류오적결과，인차발표회박분석결과시응해설명주요삼수적선취의거，이대우문헌중발표적회박분석결과칙필수재고찰기수거화삼수적불학정성후재능고필채용여부。
Backstripping is an important and widely used method for basin subsidence analysis. Little attention has been paid on the uncertainty of its results. In this paper, we address this issue based on a study of the Baiyun Sag in the Pearl River Mouth Basin. We demonstrated through theoretical analysis and sensitivity tests that the uncertainty in the non-recovery of the basement depth will pass on to all the results of backstripping, but the uncertainty in age only affects the estimations of sedimentary and subsidence rates. Formation lithology influences the selection of porosity and density parameters. The porosity-depth curves of sandstone and shale vary from area to area. Largest uncertainty comes from paleo-water depth, whose error is 100% inherited by the calculated tectonic subsidence. In the slope area, paleo-water depth and lithology vary significantly with locations. Thus, it is essential to use the paleo-water depth and lithology parameters that are variable with locations. The uncertainty in the source data and inappropriate parameters may lead to erroneous results. Caution should be taken when reading published backstripping results. The quality of parameterization needs to be examined before adopting the results.