TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents a new method for determining formation resistivity via sequential interpretation of the LWD and Wireline (WL) resistivity logs. The LWD logs can be used to determine the Rt, but they may not contain enough information to accurately determine parameters of invaded zones. The inversion-based interpretation of the WL Array resistivity logs provides a direct way of determining the hydrocarbon-bearing formation model. However, interpretation of WL data may be unstable and provide an incorrect equivalent solution due to a strong non-uniqueness of the inverse problem. To find the true model from an unlimited number of equivalent solutions, we propose a stable method that leads to a gradual increase of the formation model complexity.The major steps are:1. Estimation of Rt using deep-reading LWD data inversion. 2. Estimation of Rxo using an Rxo WL log. 3. Estimation of Lxo using WL data inversion. 4. Simultaneous corrections of the final model parameters using WL data inversion.To establish the effectiveness of our method, we first successfully tested it on 2-D and 3-D benchmark models. To examine the practical validity of the method, we applied it to LWD induction data and the Array Lateral Log WL data acquired in a salt-saturated mud environment in a deviated well located in the South China Sea. Our objective was accurate determination of hydrocarbon saturations. Application of our method allowed us to accurately determine the formation resistivity and translate it directly to accurate Sw estimates. We demonstrate that the suggested method provides a lower Sw saturation than the sole WL data interpretation.
The use of drill cuttings in the reservoir characterization can help to understand the reservoir properties. This is promoted by the need of near-real time formation parameters to calibrate the logs acquired while drilling and/or in horizontal wells where conventional coring is not an option. Similar to the cores, the measurements performed on cuttings are always challenged against both experiments and interpretation procedures, however with larger margins of uncertainties. We focus this study on measuring the cutting porosity and pore size distributions to highlight the impacts of cutting size on the reliability of the results to represent the actual formation porosityespecially for complex rocks. We determined the porosity using the solid and the pore volumes of drill cuttings obtained from sandstone and carbonate rocks. After cleaning and drying, the solid volume is measured using a gas pycnometer. The pore volume is then measured using NMR T2 relaxation in saturated surface dry drill cuttings (SSD). The porosity and pore size distributionsmeasured on sandstones and carbonates cuttings (down to 1 mm) matched very well the core measured values. The complexity of the rock, though, is found deterministic for reliability of the cuttings especially for the carbonates at reduced cutting sizes. We also emphasized on the effects of the water-film that forms on the surface of the cuttings on porosity readings.
Mud loggers are the first (and sadly in some cases the only) people to look at the cuttings. To actually see what the rocks look like, feel like, occasionally even taste. Most people looking at a well will actually look at "wriggly lines" or at best the cuttings descriptions from the loggers or geologist, two or three lines of abbreviations "claystone, light grey to grey, soft to firm, occasionally hard, slightly calcareous, trace fine sand". We have all read them, many of us have written them. These descriptions are incredibly useful and valuable, they are often all we have to understand the actual rocks and geology, especially with older wells. But in a world where we now enter the description and draw the logs with a computer, this information still comes from the subjective view of the logging geologist peering through a microscope In recent years, several tools have been developed to analyze drill cuttings from oil and gas wells. The most commonly used tools include X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM) combined with energy dispersive X-ray spectroscopy (EDX), bulk density, and pyrolysis. Although each of these tools can be used to develop a limited determination of the in-situ rock character, the combination of three of these tools (XRF, SEM/EDX, and pyrolysis) can provide a more comprehensive picture of formation properties.The combination of XRF analysis with the SEM/EDX analysis is the key to the cuttings workflow. The exact location within the borehole can be determined and a robust mineralogy developed that is independent of normative mineralogy (typical XRF) or operator-interpretive mineralogy (XRD). Additional outputs include relative brittleness index, bulk density, lithology, fractional and textural relationships, total organic carbon (TOC) proxy, and a new porosity index. Trace and major elemental ratios are also available for precise stratigraphic placement. The addition of cuttings pyrolysis enables hydrocarbon typing, producible hydrocarbons, TOC, and total inorganic carbon (TIC) within each sample to be established.Chemical Lithostratigraphy uses whole rock inorganic geochemical (elemental) data, to give information on: Extrabasinal source area dominance and origin (volcanic, metamorphics, igneous, sedimentary), Extrabasinal component weathering or diagenesis (cementation) Intrabasinal components (Palaeoenvironment and insitu origin of sediments) Chemical Lithostratigraphy analysis of cuttings can be done application of automated mineralogical analysis of cuttings samples pre-drilling in defining stratigratic zones via mineralogy/elemental data. And then explore the application of the same data to assist, and in this case lead, the decision making process during directional drilling of the lateral well. The paper will also look at the use of the technology in defining tactical fracc-ing zone based on rock properties (e.g. ductility) determined from the mineralogical, elemental and textural data.This paper will show that through the use of automat...
Detailed reservoir characterization is the main objective of all petrophysical measurements. The information obtained from petrophysical logs and well testing measurements is integrated with core-based sedimentological studies and core analysis measurements. Core-based information is crucial in the exploration phase of a field because it enables an extensive understanding of the reservoir rock potential. To reduce the operational time and cost, conventional full-core acquisition programs are often curtailed and operators rely on sidewall coring. Rotary sidewall cores provide accurate depth-controlled core plugs in various lithologies in a quicker and cost-effective way. A new rotary sidewall coring tool has been utilized in Saudi Arabia that enables recovery of high-quality core plugs even from small-sized boreholes. The acquired core plugs have sufficient size for use in conventional and special core analysis, and petrographic studies. The capability to recover up to 60 samples in a single trip enables good coverage of the different lithologies during one acquisition. The core acquisition time per sample is significantly improved over previous generation tools, thus enabling a significant reduction in coring operation time. In addition, the ability to obtain 60 samples in one run enables operators to modify their core-acquisition programs, as sidewall cores provide a good alternative if conventional core programs are not properly executed. This paper reviews experience and examples where rotary sidewall cores were obtained from several clastic and carbonate formations from different fields in various locations within Saudi Arabia. The operational environments and borehole conditions in which sidewall cores were obtained were exceedingly heterogeneous. These cases include very hard sandstones, mixed sand and shale layers, and limestone to dolomitic carbonates.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents a new method for determining formation resistivity via sequential interpretation of the LWD and Wireline (WL) resistivity logs. The LWD logs can be used to determine the Rt, but they may not contain enough information to accurately determine parameters of invaded zones. The inversion-based interpretation of the WL Array resistivity logs provides a direct way of determining the hydrocarbon-bearing formation model. However, interpretation of WL data may be unstable and provide an incorrect equivalent solution due to a strong non-uniqueness of the inverse problem. To find the true model from an unlimited number of equivalent solutions, we propose a stable method that leads to a gradual increase of the formation model complexity.The major steps are:1. Estimation of Rt using deep-reading LWD data inversion. 2. Estimation of Rxo using an Rxo WL log. 3. Estimation of Lxo using WL data inversion. 4. Simultaneous corrections of the final model parameters using WL data inversion.To establish the effectiveness of our method, we first successfully tested it on 2-D and 3-D benchmark models. To examine the practical validity of the method, we applied it to LWD induction data and the Array Lateral Log WL data acquired in a salt-saturated mud environment in a deviated well located in the South China Sea. Our objective was accurate determination of hydrocarbon saturations. Application of our method allowed us to accurately determine the formation resistivity and translate it directly to accurate Sw estimates. We demonstrate that the suggested method provides a lower Sw saturation than the sole WL data interpretation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.