Combining Nuclear Magnetic Resonance with Deep and Ultradeep Azimuthal Resistivity Images in Carbonate Reservoirs Links Reservoir Structure with Rock Type while Drilling

Author:

Ramadan Osama1,Idris Umar1,Van Steene Marie2,Santoso Gagok2

Affiliation:

1. Saudi Aramco

2. Schlumberger

Abstract

AbstractDeep and ultradeep azimuthal resistivity images enable precise well placement inside the reservoir structure. However, they deliver limited information about the quality of the reservoir, especially in carbonates, where large pore-size variations are common. Combining the deep and ultra-deep resistivity images with logging-while-drilling (LWD) nuclear magnetic resonance (NMR) measurements enables linking reservoir structure with rock types while drilling for optimal well placement.The NMR data is used to generate four petrophysical rock types while drilling: RT-1 has good porosity and long T2 components, indicating large pores; RT-2 has good porosity but medium T2 components, indicating smaller pores; RT-3 has medium porosity and long T2 components; and RT-4 has medium or low porosity and medium or short T2 components, indicating the worst facies. The first step in identifying these rock types is running factor analysis on the NMR data. This data analysis method is used to reduce a large dataset to a smaller number of underlying components. Used with NMR data, the method typically produces 9 to 11 factors and their associated poro-fluid facies, which are further reduced to four to ease interpretation.The method was implemented in two wells. The first had a single lateral, which was geosteered using ultradeep azimuthal resistivity images and NMR. The borehole entered the reservoir from the bottom. The NMR indicated a large section of RT-4, so the well was steered to cross into the upper reservoir lobe in search of better rock type. The best rock type, RT-2, was discovered at 8 ft true vertical depth (TVD) below the top of the reservoir, and geosteering continued within that rock type.The second well was a trilateral, geosteered with deep azimuthal resistivity imaging and NMR measurements. The initial lateral penetrated the first reservoir layer, where the NMR indicated RT-3 rock type with high permeability. After about 500 ft of drilling, the target reservoir layer was identified below the wellbore, and the well was steered into it. The NMR initially indicated that the rock type was RT-2, but combining the reservoir structure from the deep azimuthal resistivity image inversion with NMR rock typing confirmed that the upper section of the second layer had the best rock type, namely RT-1. Based on this finding, the second and third laterals were placed in the upper part of the same reservoir layer, with an excellent net-to-gross ratio.Association of NMR rock typing and reservoir structure while drilling is a new methodology that combines the strengths of both techniques to optimize reservoir understanding and well placement.

Publisher

SPE

Reference3 articles.

1. Hursan, G., Silva, A., Van Steene, M., 2020. Learnings from a New Slim Hole LWD NMR Technology. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference (ADIPEC), Abu Dhabi, UAE, 9-12 November. SPE-202897-MS. https://doi.org/10.2118/202897-MS.

2. Jain, V., Cao Minh, C., Heaton, N., 2013. Characterization of Underlying Pore and Fluid Structure Using Factor Analysis on NMR Data. Paper presented at the SPWLA 54th Annual Logging Symposium, New Orleans, Louisiana, USA, 22-26 June. SPWLA-2013-TT.

3. High-Fidelity Real-Time Imaging with Electromagnetic Logging-While-Drilling Measurements;Thiel;IEEE Transactions on Computational Imaging,2017

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