Improved Integrated Reservoir Interpretation Using Gas While Drilling Data

Abstract

Summary The acquisition of gas in mud data while drilling for geological surveillance and safety is an almost universal practice. This source of data is only rarely used for formation evaluation because of the widely accepted presumption that it is unreliable and unrepresentative. Recent developments in the mud-logging industry to improve gas data acquisition and analysis have led to the availability of better quality data. Within a joint Elf/Eni-Agip Div. research program, a new interpretation method has been developed following the comprehensive analysis and interpretation of gas data from a wide range of wells covering different types of geological, petroleum, and drilling environments. The results, validated by correlation and comparison with other data such as logs, well tests, and pressure/volume temperature (PVT) data, enable us to characterize lithological changes; porosity variations and permeability barriers; seal depth, thickness, and efficiency; gas diffusion or leakage; gas/oil and hydrocarbon/water contacts; vertical changes in fluid over a thick monolayer pay zone; vertical fluid differentiation in multilayer intervals; and biodegradation. The comparison of surface gas, PVT, and geochemistry data clearly confirms the consistency between the drilling gas data (gas shows) and the corresponding reservoir fluid composition. The near real-time availability, at no extra acquisition cost, of such data has led to: The optimization of future well operations (such as logging and testing). A better integration of while-drilling data to the well evaluation process. Asignificant improvement in both early formation evaluation and reservoir studies, especially for the following applications, in which traditional log analysis often remains inconclusive: Very-low-porosity reservoirs. Thin beds. Dynamic barriers and seal efficiency. Low-resistivity pay. Light hydrocarbons. Examples show gas while drilling (GWD) wellsite quicklook interpretations with simple lithological and fluid interpretations, as well as more complex reservoir and fluid characterization applications in varied geographical and geological contexts; both demonstrate how GWD data are integrated with more standard data sets.