Carbonate Reservoir Rock Typing and Mapping from the Horizontal Well High Resolution Logging While Drilling Images

Author(s):  
S. Yang ◽  
R.H. Al Lawatia
2021 ◽  
Author(s):  
Shiduo Yang ◽  
Thilo M. Brill ◽  
Alexandre Abellan ◽  
Chandramani Shrivastava ◽  
Sudipan Shasmal

Abstract Fracture evaluation and vuggy feature understanding are of prime importance in carbonate reservoirs. Commonly the related features are extracted from high resolution borehole images in water-based mud environments. To reduce the formation damage from drilling fluids, many wells are drilled with oil-based muds (OBM) in carbonate reservoirs. There are no appropriate measurements to resolve the reservoir characterization in OBM with the existing technologies in horizontal wells—especially in real-time—to make decisions at an early stage. In this paper, we would like to introduce a workflow for geological characterization using a new dual-images logging while drilling tool in oil-based mud. This new tool provides high resolution resistivity and ultrasonic images at the same time. Structural features, such as bedding boundaries, faults, fractures can be identified efficiently from resistivity images; while detailed sedimentary features, for example, cross beddings, vugs, stylolite are easily characterized using ultrasonic images. Benefiting from the dual images, an innovative workflow was proposed to estimate the vug feature more accurately; and the fractures can be identified from images and classified based on tool measurement principles. One case study from the Middle East demonstrated the benefits of this new measurement. A near well structure model was constructed from bed boundaries picked from borehole images. The fractures were picked and classified confidently using the dual images. Additionally, fracture density statistics are available along the well trajectory. The vug features were extracted efficiently, which indicates the secondary porosity development information. Rock typing is achieved by combining fracture and vug analysis to provide zonation for completion and production stimulation. The dual-images provide the capability for geological characterization in carbonate reservoir in an oil-based mud environment. The image-based rock typing helps segment the drain-hole for completion and production stimulation. The reservoir mapping with rock typing provides detailed information for in-filling well design.


2021 ◽  
Vol 11 (4) ◽  
pp. 1577-1595
Author(s):  
Rasoul Ranjbar-Karami ◽  
Parisa Tavoosi Iraj ◽  
Hamzeh Mehrabi

AbstractKnowledge of initial fluids saturation has great importance in hydrocarbon reservoir analysis and modelling. Distribution of initial water saturation (Swi) in 3D models dictates the original oil in place (STOIIP), which consequently influences reserve estimation and dynamic modelling. Calculation of initial water saturation in heterogeneous carbonate reservoirs always is a challenging task, because these reservoirs have complex depositional and diagenetic history with a complex pore network. This paper aims to model the initial water saturation in a pore facies framework, in a heterogeneous carbonate reservoir. Petrographic studies were accomplished to define depositional facies, diagenetic features and pore types. Accordingly, isolated pores are dominant in the upper parts, while the lower intervals contain more interconnected interparticle pore types. Generally, in the upper and middle parts of the reservoir, diagenetic alterations such as cementation and compaction decreased the primary reservoir potential. However, in the lower interval, which mainly includes high-energy shoal facies, high reservoir quality was formed by primary interparticle pores and secondary dissolution moulds and vugs. Using huge number of primary drainage mercury injection capillary pressure tests, we evaluate the ability of FZI, r35Winland, r35Pittman, FZI* and Lucia’s petrophysical classes in definition of rock types. Results show that recently introduced rock typing method is an efficient way to classify samples into petrophysical rock types with same pore characteristics. Moreover, as in this study MICP data were available from every one meter of reservoir interval, results show that using FZI* method much more representative sample can be selected for SCAL laboratory tests, in case of limitation in number of SCAL tests samples. Integration of petrographic analyses with routine (RCAL) and special (SCAL) core data resulted in recognition of four pore facies in the studied reservoir. Finally, in order to model initial water saturation, capillary pressure data were averaged in each pore facies which was defined by FZI* method and using a nonlinear curve fitting approach, fitting parameters (M and C) were extracted. Finally, relationship between fitting parameters and porosity in core samples was used to model initial water saturation in wells and between wells. As permeability prediction and reservoir rock typing are challenging tasks, findings of this study help to model initial water saturation using log-derived porosity.


2021 ◽  
Vol 6 (4) ◽  
pp. 62-70
Author(s):  
Mariia A. Kuntsevich ◽  
Sergey V. Kuznetsov ◽  
Igor V. Perevozkin

The goal of carbonate rock typing is a realistic distribution of well data in a 3D model and the distribution of the corresponding rock types, on which the volume of hydrocarbon reserves and the dynamic characteristics of the flow will depend. Common rock typing approaches for carbonate rocks are based on texture, pore classification, electrofacies, or flow unit localization (FZI) and are often misleading because they based on sedimentation processes or mathematical justification. As a result, the identified rock types may poorly reflect the real distribution of reservoir rock characteristics. Materials and methods. The approach described in the work allows to eliminate such effects by identifying integrated rock types that control the static properties and dynamic behavior of the reservoir, while optimally linking with geological characteristics (diagenetic transformations, sedimentation features, as well as their union effect) and petrophysical characteristics (reservoir properties, relationship between the porosity and permeability, water saturation, radius of pore channels and others). The integrated algorithm consists of 8 steps, allowing the output to obtain rock-types in the maximum possible way connecting together all the characteristics of the rock, available initial information. The first test in the Middle East field confirmed the applicability of this technique. Results. The result of the work was the creation of a software product (certificate of state registration of the computer program “Lucia”, registration number 2021612075 dated 02/11/2021), which allows automating the process of identifying rock types in order to quickly select the most optimal method, as well as the possibility of their integration. As part of the product, machine learning technologies were introduced to predict rock types based on well logs in intervals not covered by coring studies, as well as in wells in which there is no coring.


2010 ◽  
Author(s):  
Hani Al-Sahn ◽  
Amaud Mayer ◽  
Ibrahim Al-Ali ◽  
Habeeba Al-Housani ◽  
Fathy El-Wazeer

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