Characterizing the Greater Burgan Field With Geochemical and Other Field Data

Abstract

Summary This paper describes recent results from an ongoing geochemical study of the supergiant Greater Burgan field, Kuwait. Oil occurs in a number of vertically separated reservoirs including the Jurassic Marrat reservoir and Cretaceous-Minagish, -Third Burgan, -Fourth Burgan, -Mauddud, and -Wara reservoirs. The Third and Fourth Burgan sands are the most important producing reservoirs. Over 100 oils representing all major producing reservoirs have been analyzed using oil fingerprinting as the principal method, but also supported by gravity, sulfur, and pressure-volume-temperature (PVT) measurements. From a reservoir management perspective, an important feature of the field is the approximately 1,200-ft-long hydrocarbon column which extends across the Burgan and Wara reservoirs. Oil composition varies with depth in this thick oil column. For example, oil gravity varies in a nonlinear fashion from about 10°API near the oil/water contact to about 39°API at the shallowest Wara reservoir. This gravity-depth relationship makes identification of reservoir compartments solely from fluid property data difficult. Including oil geochemistry in the traditional mix of PVT and production logging data improves the understanding of compartmentalization and fluid flow in the reservoir, both in a vertical and lateral sense. The composition of reservoir fluids is controlled by a number of geological and physical processes. We attempted to identify unique sets of geochemical parameters that were sensitive to specific oil alteration processes. One set of geochemical properties correlated strongly with gravity and is, therefore, related to the gravity-segregation process. A second set of parameters showed essentially no correlation with gravity or depth but established unique oil fingerprints for most of the major producing reservoirs and identified a number of different oil groups within the Burgan and Wara reservoirs. We interpret the presence of these oil groups to indicate reservoir compartments owing to laterally continuous shales and faults which act as seals on a geologic time frame. More tentative is the identification of production time frame barriers from the fluid composition data. The oil fingerprint data have been used to distinguish oils from the major producing reservoirs and evaluate hydrocarbon continuity within the reservoirs. Introduction This article describes a geochemical study of oils from the Greater Burgan field, Kuwait. During this study, we examined the compositional variation of oils within the field to evaluate reservoir continuity. This study is part of a larger project to describe the producing characteristics of the major reservoirs in the Burgan field en route to applying the best practices in the overall reservoir management program. In Phase I of this study,1 approximately 60 oils from the Burgan, Magwa, and Ahmadi areas of the Greater Burgan field were analyzed using oil fingerprinting. The objective was to determine if oils from the Wara, Third Burgan, and Fourth Burgan reservoirs had unique oil fingerprints and to evaluate oil mixing because of wellbore communications. In Phase II, a larger suite of wells was sampled to broaden the coverage of the field, both areally and stratigraphically, as shown in Fig. 1. Even though a considerably larger number of wells were sampled in Phase II, the sampling density still remains rather coarse in this supergiant field, spanning 320 sq mile. A variety of different techniques are available for reservoir geochemistry studies.2 The principle method used in this study is whole-oil gas chromatography; sometimes referred to as oil fingerprinting. This method has been described before3 and is, therefore, summarized only briefly here. Oil samples were collected at the wellhead, at atmospheric conditions, and analyzed using capillary gas chromatography. A standard of about 200 calibrated peak heights was developed and from this about 30 standard peak height ratios were calculated. These ratios were selected based on their ability to separate the oils into uniquely different groups. Two different multivariate statistical techniques were used to analyze the chromatography data: cluster analysis and principal components analysis. Both techniques were used to identify groups of similar oils based on the peak height ratios. Petroleum is a very complex natural product whose composition is controlled by various geologic processes which occur both before and after fluid accumulation. In our geochemical studies of the Burgan field, we have used the composition of the produced oil to study the hydrocarbon connectivity of different reservoirs. Some measurements, such as oil gravity, gas/oil ratio and bubblepoint data, characterize the bulk properties of the fluid. Other measurements, such as the hydrocarbon fingerprint, are based on the molecular composition of the fluid. Both types of data are necessary to completely characterize a petroleum reservoir, but the molecular composition data are frequently a more sensitive measure of the reservoir connectivity. Where available, both types of data have been used in this study of the Burgan field. The identification of reservoir compartments, both vertical and lateral, is a necessary component of efficient reservoir appraisal and management. Reservoirs are compartmentalized when barriers to fluid flow are present which prevent fluid communication between different parts of the reservoir. Smalley and Hale have discussed the need for early identification of reservoir compartments well in advance of dynamic production measurements.4 Some barriers are effective on a geologic time scale and frequently result in separate oil pools with unique oil/water contacts and initial pressure gradients. Other barriers may become effective on a production time frame. These are typically identified only after the field is put on production. Reservoir fluid composition data have most frequently been interpreted as indicators of geologic time-frame compartments, but it may provide an early indication of production time-frame compartments in some cases. The Greater Burgan Field The Greater Burgan oil field lies within the Arabian basin in the state of Kuwait. General reviews of the geology and producing history of the field are described by Brennan,5 Kirby et al.,6 and Carman.7 The field is subdivided into the Burgan, Magwa, and Ahmadi sectors based on the presence of three structural domes as shown in Fig. 1. The boundary between the northern Magwa/Ahmadi and the Burgan sectors is the Central Graben fault complex, as shown in Fig. 2.

A Geotechnical and Geochemical Characterisation of Oil Fire Contaminated Soils in Kuwait

“…The Greater Burgan field is the largest clastic oil field in the world covering an area of 838km 2 , located in south eastern Kuwait. The oil field is subdivided into the Burgan, Magwa and Ahmadi sectors based on the underlying geological structure (Kaufman et al, 2000). At the height of the destruction smoke plumes from the Greater Burgan oil fires extended over 50km from the well sites up to an altitude of 2.5km.…”

Reservoir compartmentalization: get it before it gets you

“…Kaufman et al 1990a;Elshahawi et al 2005) or recent external processes affecting the reservoir (e.g. Montel et al 1993;Berg et al 1994;Zawisza 2004), if they diverge from a steady state distribution.…”

“…Such 'fingerprinting' studies might identify statistical differences in fluid composition or pressure between different parts of a field, and use that as an indicator of compartmentalization (e.g. Kaufman et al 1990a, b;Stølum & Smalley 1992;Stølum et al 1993;Hwang & Baskin 1994;.…”

Maximizing volumetric sweep efficiency in waterfloods with hydrocarbon F–Φ curves

“…Interwell connectivity, in waterfloods, has been determined qualitatively using natural tracers and other geochemical fingerprinting. Some of the useful studies that appear in the literature in this context are presented by Smalley et al (1994), Westrich et al (1999), and Kaufman et al (2000Kaufman et al ( , 2002, among others. Recently capacitance-resistance models (CRMs) were introduced to map the interwell connectivity between producers and injectors (Izgec and Kabir, 2009;Sayarpour et al, 2009;Yousef et al, 2006).…”