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Understanding the hydraulic properties of reservoir rocks is crucial for estimating reserves or managing storage and production of a reservoir. In reservoirs containing complex carbonates, rock-typing methodologies that recognize multimodal porosity have been widely used. A new rock-typing workflow based upon Thomeer-buoyancy modelling is presented...
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... hydrocarbons migrate into a trap, buoyancy forces exerted by the lighter hydrocarbon will displace the in-situ water that previously occupied the pore space (Fig. 3). However, not all water is displaced; some will be held by capillary forces within the pore system. Narrower capillaries, those pore systems dominated by smaller pore throats, hold onto the water most ...
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The main purpose of comprehensive reservoir characterization is to reliably calculate, characterize and identify petrophysical parameters including porosity, permeability, rock fabrics, pore size distribution, pore network system, saturation and capillary pressure. These essential petrophysical properties could be achieved by a combination of Nucle...
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Citations
... Because most of the carbonate fields display a high degree of heterogeneity and complex structures, the ability to understand the complex micritic pore structure of the carbonate properties is relevant to developing an accurate knowledge of the formation properties having an impact on production; namely S w , permeability, relative permeability, wettability and recovery factors [30,31]. One of the factors crucial to estimating the reserves of the reservoir, and managing storage or the reservoir's production also lies in understanding the hydraulic properties of the reservoir rocks [32]. In converting laboratory properties into subsurface conditions, permeability modelling should be followed with a well-established laboratory route to curb any ambiguity arising from laboratory data management [33,34]. ...
Saturation Height Modelling (SHM) is an important reservoir characterization method for estimating the water saturation component which is a fraction of the total reservoir fluids in porous media. Although several methods have been used in calculating water saturation, little or no research has employed Response Surface Methodology (RSM) in predicting water saturation in field cores. In this paper, well datasets were tested with four conventional curve fitting models including Lambda, Thomeer, Leverette J, and Brooks-Corey of which Brook-Corey gave the best fit with an R2 of 0.485. The RSM with the Central Composite Design (CCD) was used to obtain the mathematical and statistical relationship between the predictors and target as well as the variables’ interactions optimization. The model was analysed using Analysis of Variance (ANOVA) which validated the correlations with an F-value of 4.96, a p-value less than 0.05, and a Lack of Fit-value of 0.76 implying that the model developed was statistically significant. The RSM model gave a better fit with an R2 value of 0.817 with mathematical links, almost twice that predicted by the conventional methods. Then, the testing performance of the RSM model was compared to the standard radial basis function neural network model (R2 of 0.9779). The results proved that both RSM and RBFNN models’ performance was accurate and reliable and could give a precise prediction of water saturation without any conventional curve fitting parameters.
... The application to PSD of curves fitting methods such as Thomeer's multiple Hyperbolae, [Clercke & al.;2008;Smart & al.,2016], Dual Gaussian or Dual Lorentzian [Xu, C. & Torres-Verdin, C.;2013], raises controversies [Theologou & al.;2015]. Besides, "the shape of the [PSD] curve near the threshold pressure has a greater effect on permeability than curve shape at high capillary pressures. ...
Abstract
Aiming to improve the characterization of Carbonate Reservoirs from resource assessment to optimization of the static and dynamic modeling, we describe a holistic flowchart for an integrated approach by using the capillary pressure measurements. Its most innovative steps from pore scale to field scale is illustrated on a Super Giant Carbonate Reservoir from the Middle East.
The flowchart relies on patented, published and proven “data driven” algorithmic techniques (k-NN, Histogram Upscaling and MRGC-CFSOM clustering) devoid of any user’s bias. Its capability to integrate Static and Dynamic, from Pore Scale to Log scale, stems from the integration, prediction and upscaling at log scale, over cored and un-cored intervals of MICP curves together with all core and log material. Predictions by means of “k-NN multiple modeling” of SCAL & RCA plug measurements allows a reliable and accurate characterization of the rock matrix at log scale, while quantifying its degree of heterogeneity. By revealing to the geoscientists, the pore scale rock texture, its stratigraphic evolution and its heterogeneities, the continuous profile of upscaled Pore Size Distribution (PSD) curves vs logs provides invaluable information on the rock forming processes controlling the matrix Porous Network.
By applying the Purcell theory onto the upscaled PSD, the “Log scale” Permeability and the true FZI and Rmh are computed which are then used as input to a e-Facies model (MRGC-CFSOM) by integrating to other logs and core material. The e-Facies model is interpreted in terms of “matrix”
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storage and flow parameters as well as in terms of depositional mechanisms and diagenetic overprints, in the light of the core descriptions whose Petrophysical pertinence is thoroughly and quantitatively validated with all the Petrophysical material.
By reversing the method used to derive PSD from MICP saturation curves and using the Pc equating the buoyancy forces at any depth increment, the saturation at any depth increment above the actual Free Water Level (or a scenario of FWL), is computed from the continuous profile of upscaled PSD. Production data, RSTs and PLTS provide the information on total flow and by subtracting matrix contribution to the total flow, the location and quantification of the contribution of the depth intervals with large vugs and fractures is greatly eased, particularly if Borehole imagery is available. The contribution of Matrix, large vugs and fractures are then merged into a single model used for robust well to well correlations, zonation of the reservoir, 3D gridding and volumetric evaluation.
Using this innovative flowchart approach, characterization of high permeability streaks, saturation height function and chemical polymer EOR
... Inversion over the third porous body also shows decreasing of resistivity, but it doesn't change the saturation that much due to the change of rock type and pore geometry. In this case, the Thomeer-buoyance model is recommended for better understanding of saturation (Smart, 2016). ...
The Archie equation is the most common approach for calculating water saturation. The true formation resistivity that is derived from resistivity logs is an important component. In high-angle or horizontal wells (Ha/Hz) the commonly employed induction style tools and multi-propagation resistivity (MPR) tools employed in logging-while-drilling (LWD) have challenges. In particular, at bed boundaries, the formation-to-wellbore geometry affects deep-reading logs and generates artifacts such as so-called polarization horns on the logs. These effects become more significant with increases in the relative dip and the resistivity contrast between the beds. These conditions impair the use of resistivity for water saturation determination. An innovative modeling workflow to generate a true formation resistivity (Rt) from LWD MPR logs is presented. In addition, a number of case examples from Abu Dhabi reservoirs are portrayed.
The workflow described in this study begins with the interpretation of borehole image data to build a structural earth model. For this, the picked boundaries are extended away from the trajectory within an investigative volume of the MPR responses and are used to constrain an inversion algorithm that solves for Rt. The inversion is conducted using eight short- and long-spaced apparent phase differences and attenuation data. Different starting models and inversion constraints are applied to evaluate the sensitivity of the inversion results. The inversion results are further qualified from the ‘misfit’ calculated by the inversion algorithm.
This methodology was used to process data from multiple wells in a development field near Abu Dhabi. These high-angle wells are from carbonate reservoirs with varying characteristics (such as tight, layered, high-permeability streaks, etc) and all employ LWD measurements. The integrated data of vertical wells formation evaluation, dean stark and dynamic data (well test) were used to validate results of the case study.
The processing results showed significant improvement in determining true resistivity that provided highly coherent saturation determination along the entire wellbore profile. It gave confidence in the effectiveness of the approach for an improved quantitative petrophysical evaluation in Ha/Hz wells.
This new processing method is able to solve the existing issue associated with LWD measurement in high angle wells thereby improving the saturation calculation significantly.
Carbonate reservoir complexity imposes some challenges in formation evaluation and characterization. Grain, pore, and throat size distributions play major roles in rock typing to understand static and dynamic behaviors of carbonate reservoirs. Special core analysis techniques, such as MICP and digital core imaging, revealed that the presence of different types of pore structures can be classified based on sizes as micro, meso and macro pores. This paper explores a unique inversion technique using nuclear magnetic resonance (NMR) data to deliver fast, accurate, and continuous pore typing across logged intervals.
The traditional NMR data processing technique consists of sequential steps that ultimately convert echoes from time domain into T2 domain using an exponential inversion, also known as Laplace transform. NMR-gamma inversion (NMR-GI) workflow is a mathematical approach to process the NMR data using probabilistic functions. The gamma inversion function has a form of a bell curve with the base in the logarithmic x-axis. Unlike exponential inversion technique, this inversion produces multiple components. Each component is located at a particular time and it is labeled with a specific number, which reflects the T2 time stamp of each component. The individual area under each component is translated into porosity units.
The application of gamma inversion in a T2 spectrum results in subcomponents via deconvolution of the original spectrum. The display of the components makes it easy to visually analyze and interpret the porosimetry for pore size distribution and group the components for pore typing.
A deeper look into the different components of the T2 spectrums enlarges the NMR measurement portfolio by displaying the porosimetry and pore size distribution. The inverted T2 results from both logging while drilling (LWD) and wireline tools in different fields are consistent with the reservoir geological and petrophysical models. The added value of this technique can be tangible for geophysical and geological (G&G) applications as well as completion design optimization. The NMR-GI technique can be further utilized and calibrated to improve reservoir understanding and optimize advanced core analysis by providing a quick continuous carbonate pore and rock type log.
