不同密度-中子随钻测井工具对地层评价方法的影响

Federica Di Maggio, G. Duci, F. Pampuri
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引用次数: 0

摘要

随钻测井(LWD) Density-Neutron可以实时或接近实时地计算连续的孔隙度和页岩体积曲线。有时可以从不同的工具类型获取日志。在这些情况下,应注意单个工具的读取特征,以一致的方式校准岩石物理解释。一般来说,随钻测井解释比钢丝绳测井更为关键,因为作业时间严重限制了数据的准确质量控制。不同的核工具涉及不同的密度测量系统和不同的能量来源,以及不同的中子能量范围。在油田开发阶段,岩石物理分析可以处理不同类型的密度和中子测井,甚至在同一口井的不同阶段,这使得地层评价阶段的岩性识别、页岩体积和有效孔隙度评价更加困难,甚至会产生误导。本文的目的是通过不同的案例历史来展示不同类型的工具如何影响地层评价模型以及缓解问题的可能方法。案例研究包括来自不同井眼测井和随钻测井工具、不同井径、井斜和岩性的测井数据。经过仔细的质量控制,对数据集进行了处理,以确定均匀层段(从岩性和孔隙度的角度来看),以便仅根据不同工具类型的特征进行响应比较。一旦确定了正确比较的条件,均匀区间内的统计分布就可以使用直方图和交叉图进行定量描述。分析结果证明了岩性的影响:粉砂质页岩层序在工具响应之间表现出最显著的差异,而清洁岩性之间的差异较小或可以忽略不计。如果不适当考虑,均匀层段内不同的密度-中子(DN)工具响应会强烈影响岩石物理解释的输出,主要影响页岩体积和有效孔隙度,在油藏建模中也会产生危险的沉降。在本案例中,不同随钻密度工具的观测差异在0-0.02 gr/cc之间,而中子工具的观测差异在0-5 p.u之间。为了量化上述差异对岩石物理解释的影响,研究人员使用了一种确定性解释模型(根据岩心数据校准)来计算页岩体积和有效孔隙度。比较不同工具和伽马射线(GR)获得的DN页岩体积被定义为一种简单但具有战略意义的方法,可以理解DN响应的含义,从而在DN交叉图中定义适合岩石物理解释的页岩点。如果使用正确校准的各种工具类型获取DN测井,则测井读数之间的差异仅是由于工具特性造成的,如果岩性参数没有正确校准,则可能会误导解释。在不同的采集条件下,为了获得正确、一致的岩石物理解释,必须与其他岩性测井(例如GR)进行比较,并与岩心数据进行校准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Different Density-Neutron LWD Tools Response can Affect the Formation Evaluation Approach
Log While Drilling (LWD) Density-Neutron allow to calculate, in real/near real time, a continuous porosity and shale volume curves. Sometimes log acquisitions from different tool types are available. In these cases, attention should be paid to the reading characteristics of the individual tools, to calibrate the petrophysical interpretation in a consistent way. Generally, the LWD interpretation can be considered more critical than Wire Line Log WLL because the operation timing strongly limits an accurate QC of the data. Different Nuclear tools involve different measurement system for density and different energy source as well as different neutron energy range for neutron. During the field development phase, the petrophysiscal analysis can deal with various type of Density and Neutron log, even in distinct phases of the same well, making the lithology recognition, the shale volume and the effective porosity evaluation more difficult and even misleading during the formation evaluation step. The aim of this paper is to show through different case histories, how the various tool types can affect the formation evaluation model and a possible approach to mitigate the problem. The case study includes logs from different WLL and LWD tools, different well diameters, deviations and lithologies. After a careful QC, the data sets have been processed in order to identify homogeneous intervals (from the lithology and the porosity point of view) in order to make the response comparison based only on the characteristic of the different tool types. Once the conditions for a correct comparison have been fixed, the statistical distribution within the homogeneous intervals was quantitatively described using histograms and cross-plots. The results of the analysis have proven the influence of lithology: silty-shale sequences show the most significant discrepancy between the tool responses, while the clean lithologies show less or negligible discrepancy. If not properly considered, the different Density-Neutron (DN) tool responses inside a homogeneous interval can strongly affect the output of the petrophysical interpretation, mostly on shale volume and effective porosity with a dangerous fallout also in the reservoir modelling. In the presented case study, the observed discrepancy from different LWD Density tool can vary between 0-0.02 gr/cc while for Neutron tools between 0-5 p.u. To quantify the impact of the mentioned discrepancies on the petrophysical interpretation, a deterministic interpretation model (calibrated against cores data) was used for shale volume and effective porosity calculation. The comparison between DN shale volume derived from different tools and Gamma Ray (GR) has been defined as simple but strategic approach to understand the meaning of the DN response and therefore to define the proper shale point in the DN cross-plot for the petrophysical interpretation. If DN logs are acquired with various tool types properly calibrated, the discrepancy between the log readings is only due to the tool characteristics, and may mislead the interpretation if the lithological parameters are not properly calibrated. Comparison with other lithological logs (e.g. GR) and calibration with core data is mandatory for a correct and consistent petrophysical interpretation when different acquisitions are available.
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