Intelligent methods for predicting nuclear magnetic resonance of porosity and permeability by conventional well-logs: a case study of Saharan field

2017 ◽  
Vol 10 (24) ◽  
Author(s):  
Rafik Baouche ◽  
Tahar Aïfa ◽  
Kamel Baddari
Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 518
Author(s):  
Reza Rezaee

A nuclear magnetic resonance (NMR) logging tool can provide important rock and fluid properties that are necessary for a reliable reservoir evaluation. Pore size distribution based on T2 relaxation time and resulting permeability are among those parameters that cannot be provided by conventional logging tools. For wells drilled before the 1990s and for many recent wells there is no NMR data available due to the tool availability and the logging cost, respectively. This study used a large database of combinable magnetic resonance (CMR) to assess the performance of several well-known machine learning (ML) methods to generate some of the NMR tool’s outputs for clastic rocks using typical well-logs as inputs. NMR tool’s outputs, such as clay bound water (CBW), irreducible pore fluid (known as bulk volume irreducible, BVI), producible fluid (known as the free fluid index, FFI), logarithmic mean of T2 relaxation time (T2LM), irreducible water saturation (Swirr), and permeability from Coates and SDR models were generated in this study. The well logs were collected from 14 wells of Western Australia (WA) within 3 offshore basins. About 80% of the data points were used for training and validation purposes and 20% of the whole data was kept as a blind set with no involvement in the training process to check the validity of the ML methods. The comparison of results shows that the Adaptive Boosting, known as AdaBoost model, has given the most impressive performance to predict CBW, FFI, permeability, T2LM, and SWirr for the blind set with R2 more than 0.9. The accuracy of the ML model for the blind dataset suggests that the approach can be used to generate NMR tool outputs with high accuracy.


2019 ◽  
Vol 17 (2) ◽  
pp. 328-338
Author(s):  
Xiaojun Wang ◽  
Zhenlin Wang ◽  
Cheng Feng ◽  
Tao Zhu ◽  
Ni Zhang ◽  
...  

Abstract Due to complex lithology, strong heterogeneity, low porosity and permeability; resistivity logging faces great challenges in oil saturation prediction of tight conglomerate reservoirs. First, 10 typical core samples were selected to measure and analyse the porosity, permeability, nuclear magnetic resonance (NMR) T2 spectrum and mercury injection capillary pressure (MICP) curve. Second, an empirical method was proposed for reconstructing the NMR T2 spectrum under completely watered conditions using MICP curve based on the ‘three-piece’ power function. The parameters of different models were calibrated via experimental data analysis, respectively. The 180 core experimental data from an MICP curve were used as the input database. Porosity and permeability were regarded as the MICP data selection criteria to apply this model in formation evaluation. The comparison results show good application effects. Finally, to reflect oil saturation, the ratio of T2 geometric means of NMR T2 spectra under oil-bearing and completely watered conditions was proposed. Then, the quantitative relation between oil saturation and the proposed ratio was established via experimental data from the sealed cores, which established a quantitative prediction on oil saturation of tight conglomerate reservoirs. This showed a good application effect. The average relative error and the root mean square error (RMSE) of the predicted oil saturation and sealed coring measurement were around 10 and 3%, respectively. As the proposed method is only influenced by the wettability of reservoir and viscosity of oil, it is not only appropriate for the studied area, but also for other water-wet reservoirs containing light oil. It is important for identifying oil layers, calculating oil saturation and improving log interpretation accuracy in tight conglomerate reservoirs.


2021 ◽  
Vol 73 (08) ◽  
pp. 46-47
Author(s):  
Chris Carpenter

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202683, “Marrying the Static and Dynamic Worlds: Enhancing Saturation and Permeability Interpretation Using a Combination of Multifrequency Dielectric, Nuclear Magnetic Resonance, and Wireline Formation Testers,” by Hassan Mostafa, Ghassan Al-Jefri, SPE, and Tania Felix Menchaca, SPE, ADNOC, et al., prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. Accurate water saturation evaluation and permeability profiling are crucial factors in determining volumetrics and productivity of multiple, stacked carbonate reservoirs offshore Abu Dhabi and derisking reservoir management. The case study presented in the complete paper illustrates how the integration of static measurements, such as dielectric dispersion and nuclear magnetic resonance (NMR) with dynamic measurements improves understanding of reservoir properties and supports more-accurate reservoir evaluation. Sampling and downhole fluid analysis (DFA) performed by wireline formation tester (WFT) identifies the fluid and rock properties in various flow units. Field Background and Challenges Optimal field development requires accurate estimations of water saturation and permeability. In this greenfield, the hydrocarbon is generally oil (medium to light) with very low asphaltene content. Overall, the reservoir quality is controlled by a combination of depositional environment, sequence stratigraphy, and diagenesis. Some reservoirs have good porosity, but reconciliation of log-based water saturation results with well-test results has been an issue. The objective in this case study was to drill a pilot hole for data gathering in a poorly characterized field location. Phase I included drilling a hole with a 55° deviation to cover all reservoirs for data gathering only, with the openhole reservoir section then being plugged and abandoned. Phase II of the plan was to sidetrack and complete the well as dual water-injector boreholes. In the reservoir section of the pilot borehole, a variety of logs was acquired for evaluation, including both logging-while-drilling and wireline measurements. While drilling, triple- combination data were acquired, consisting of gamma ray, resistivity, and nuclear logs (density neutron) along with resistivity images. The wireline-logging program was carried out in two stages to avoid differential sticking. In the first stage, the WFT was used to acquire 10 pressure points, seven points in the first reservoir and three points in the second. Two DFA stations were also recorded in Zone 1 to confirm whether the oil/water contact was deeper than expected. Logging was conducted using a high-tension wireline cable, which facilitates quicker accessibility to the openhole sections. In the second stage, multiple wireline runs were performed for the formation evaluation of the complete section, followed by the WFT pressure and fluid-sampling run on the drillpipe conveyance. Another critical challenge was to obtain accurate water saturations in the heterogeneous, minor, thin reservoirs, which are bounded by dense layers above and below and cause shoulder-bed effects. The third challenge in this well was to obtain an accurate, continuous, and representative permeability profile for the multiple reservoirs. WFT mini-drillstem test (DST) stations along with NMR logs were used to address this important requirement.


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