Artificial Intelligence Applied to NMR Logging for Rock and Fluid Typing in Heavy
            Oils

Rojas, Pedro; Cristea, Alexandrina; Pavlakos, Paul; Ergündüz, Okan; Keçecioğlu, Tayfun; Alpay, Server Fatih

doi:10.30632/t60als-2019_llll

Cited by 4 publications

(3 citation statements)

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“…Afterward, Zega et al and Zhang et al measured pure deoxygenated alkanes and alkane mixtures. A linear relationship between T 1, 2 and viscosity was established (Zega et al 1989;Zhang et al 1998). Latorraca et al (1999) measured highly viscous crude oils at 2 MHz.…”

Section: Introductionmentioning

confidence: 99%

“…These results applied well to moderately and highly viscous oils and are very successful at predicting the ultra-highly viscous oils. Cheng et al (2009) established a relationship between the viscosity and relaxation time for heterogeneous fluids based on the Kohlrausch-Williams-Watts function. Korb et al (2015) proposed a theory relating the longitudinal relaxation time T 1 and transverse relaxation time T 2 to the viscosity η of bulk heavy crude oils with different asphaltene concentrations.…”

Section: Introductionmentioning

confidence: 99%

“…However, the correlation did not consider the influence GOR and condensate. Zhang et al (1998) used fluid density and hydrocarbon ratio to predict HI which was adaptable to live oil. NMR is also an effective method to calculate HI.…”

Section: Introductionmentioning

confidence: 99%

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NMR fluid analyzer applying to petroleum industry

et al. 2021

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Tremendous progress of developing nuclear magnetic resonance (NMR) fluid analyzer has been witnessed in the oil industry for last two decades. This device allows extensive and accurate exploration of fluid properties, such as its hydrogen content, composition, viscosity, hydrogen index (HI), mud filtrate invasion, gas to oil ratio, average velocity, velocity distribution etc., in the situations of in situ downhole or surface Petro-pipelines. In this review article, we focus on the design principle, manufacturing, implementation, methodology and applications of NMR fluid analyzer to oil and gas industry. A detailed description of the state-of-art NMR fluid analyzers was firstly given to exhibit their respective characteristics. With these experiences on hand, we introduced a series of NMR fluid analyzers designed by us at China University of Petroleum-Beijing with continuous optimizations, in terms of magnet construction, antenna layout, circuit design and operating surroundings. These systems discussed in this article have been demonstrated to achieve multiple NMR parameter acquisition when the fluid is in stationary or flowing state. In the end, a prototype was fabricated and validated considering a vast of engineering influences, such as variable temperatures in a large range, high pressure, limited volume, detection efficiency, etc. A particular emphasis of this paper is to expedite the measurement efficiency of the NMR fluid analyzer to reduce the operation costs. This dilemma can be Figured out by upgrading both pulse sequence and observational mode. For different fluid states, two rapid pulse sequences were proposed to sufficiently obtain the multi-dimensional NMR correlation map. Meanwhile, two observational modes were developed to take full advantage of the polarization time, during which the individual antenna was systematically switched. Another domain of interest in this review concerns the applications of this new tool. For stationary fluids case, accurate identification of fluid properties is of great value for scheme building in oil and gas exploration process. Particularly, it can acquire the fluid content by different NMR responses of different components. In addition, with Bloembergen theory and Stokes–Einstein equation, not only molecular dynamics and composition, but also oil viscosity can be readily evaluated. Moreover, HI information of crude oils will be speculated through partial least square regression. As for flowing fluids case, velocity is a significant parameter to understand the in situ fluid exploitation and therefore evaluate the productivity of certain oil wells or pipelines. Regarding to the unique magnet and antenna designs in our NMR fluid analyzer; this review adopts two distinct methods to obtain flow velocity at a wide rating scale. The first one is a time-of-flight method adaptive in a homogeneous magnetic field, which is suitable in the case of fluid at high flow velocity. The other one relies on the adjacent echo phase difference at a magnetic field with constant gradient, which is preferred for relatively low flow velocity. In the near future, this tool will be tested underground to offer individual fluid velocities by combining both the stationary and flowing analysis methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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NMR fluid analyzer applying to petroleum industry

et al. 2021

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Tight Jurassic Carbonate Reservoir Characterization and Fluid Typing Identification by Integrating Magnetic Resonance, Elemental Spectroscopy and Micro-Resistivity Image Data in Umm Ross Field, West Kuwait, Case Study

Mohamed

Ali

Fahmy³

et al. 2021

Day 2 Tue, November 16, 2021

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The Middle Marrat reservoir of Jurassic age is a tight carbonate reservoir with vertical and horizontal heterogeneous properties. The variation in lithology, vertical and horizontal facies distribution lead to complicated reservoir characterization which lead to unexpected production behavior between wells in the same reservoir. Marrat reservoir characterization by conventional logging tools is a challenging task because of its low clay content and high-resistivity responses. The low clay content in Marrat reservoirs gives low gamma ray counts, which makes reservoir layer identification difficult. Additionally, high resistivity responses in the pay zones, coupled with the tight layering make production sweet spot identification challenging. To overcome these challenges, integration of data from advanced logging tools like Sidewall Magnetic Resonance (SMR), Geochemical Spectroscopy Tool (GST) and Electrical Borehole Image (EBI) supplied a definitive reservoir characterization and fluid typing of this Tight Jurassic Carbonate (Marrat formation). The Sidewall Magnetic resonance (SMR) tool multi wait time enabled T2 polarization to differentiate between moveable water and hydrocarbons. After acquisition, the standard deliverables were porosity, the effective porosity ratio, and the permeability index to evaluate the rock qualities. Porosity was divided into clay-bound water (CBW), bulk-volume irreducible (BVI) and bulk-volume moveable (BVM). Rock quality was interpreted and classified based on effective porosity and permeability index ratios. The ratio where a steeper gradient was interpreted as high flow zones, a gentle gradient as low flow zones, and a flat gradient was considered as tight baffle zones. SMR logging proved to be essential for the proper reservoir characterization and to support critical decisions on well completion design. Fundamental rock quality and permeability profile were supplied by SMR. Oil saturation was identified by applying 2D-NMR methods, T1/T2 vs. T2 and Diffusion vs. T2 maps in a challenging oil-based mud environment. The Electrical Borehole imaging (EBI) was used to identify fracture types and establish fracture density. Additionally, the impact of fractures to enhance porosity and permeability was possible. The Geochemical Spectroscopy Tool (GST) for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The integration of the EBI, GST and SMR datasets provided sweet spots identification and perforation interval selection candidates, which the producer used to bring wells onto production.

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Advanced Reservoir Characterization Using Novel NMR Technology Secures Complex Carbonate Gas Condensate Pay, A Case Study Onshore Ukraine

Rojas

Loraine

Tagarieva

et al. 2022

Day 3 Wed, May 04, 2022

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Formation evaluation in a gas condensate carbonates reservoir with high temperature and pressure is very challenging: low porosity and gas have an effect on reserve estimation and fluid typing identification. A complex of or state-of-the-art petrophysical studies were implemented for the first time in Europe in the Machukhske field in Ukraine, which helped to estimate the reservoir properties, rock quality, permeability and fluid typing of the main challenging productive carbonate reservoir of the Tournasian formation at a qualitatively new level. The 8.5" section was drilled through the Tournasian formation with oil-based mud and a composite logging suite with high pressure and temperature (P, T) ratings was deployed. Gamma Ray, Neutron, Resistivity, Density and Formation Testing tools were run along with latest generation of multifrequency, focused Nuclear Magnetic Resonance (NMR) wireline tool. Longitudinal (T1 ) and transversal relaxation time (T2) distributions were calculated from multifrequency echo trains of raw NMR data to evaluate hydrocarbon porosity and saturations. The evaluation of T2 spectra used blind source separation driven by statistical independent component analysis (BSS-ICA), a machine learning algorithm. These results were then compared against those obtained from traditional two-dimensional NMR (2D-NMR) maps, specifically the T1T2 maps, that rely on the simultaneous inversion for T1 and T2. An adequate data acquisition sequences or logging activations ensured a suitable magnitude of the borehole signal, which enabled tool to apply long polarization times needed to detect volatile fluids. Conventional logs and core data were integrated with NMR results to minimize uncertainties, mathematical artifacts, and different effects. Rock quality indicators based on NMR porosity fractions and acoustic velocities were calculated and revealed some rock heterogeneities or porosity-lithology facies. In challenging borehole condition with high P & T, high quality composite logging suite data was successfully obtained. An advanced reservoir characterization study was performed by integrating the NMR data with conventional logs which also helped to reduce the uncertainty in formation evaluation by clearly identifying pay and shale zones, deeper understanding of the storage and flow capacity of reservoir and the furthermore, providing necessary parameters for optimizing completion design. An innovative study was carried out which helped not only meet objective of the well, but also results became reference for detailing the geological and hydrodynamic models of Machukske gas condensate field. The geological and technological model of the field was updated, and further field development strategies were optimized.

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Artificial Intelligence Applied to NMR Logging for Rock and Fluid Typing in Heavy Oils

Cited by 4 publications

References 0 publications

NMR fluid analyzer applying to petroleum industry

NMR fluid analyzer applying to petroleum industry

Tight Jurassic Carbonate Reservoir Characterization and Fluid Typing Identification by Integrating Magnetic Resonance, Elemental Spectroscopy and Micro-Resistivity Image Data in Umm Ross Field, West Kuwait, Case Study

Advanced Reservoir Characterization Using Novel NMR Technology Secures Complex Carbonate Gas Condensate Pay, A Case Study Onshore Ukraine

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