Petrographic thin section images have an important role in depositional environment inference, prediction of reservoir physical properties, and oil and gas analysis. To overcome the current challenges in thin section image denoising, we propose the global residual generative adversarial network (GR-GAN). Compared with the classical generative adversarial network (GAN), the residual network structure of the GR-GAN is reconstructed, and the loss function is redefined. The GR-GAN is then applied to denoise the thin section images in two different oilfields. The final denoising results confirmed that the GR-GAN achieves the best denoising effects on both visual evaluation metrics and objective evaluation metrics compared with colour block-matching 3D filtering (CBM3D), K-singular value decomposition (K-SVD), the GAN and a fast and flexible denoising network (FFDNet). Specifically, the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) generated by the GR-GAN on the test set are 28.2410 and 0.9674, 28.1075 and 0.9443, and 27.9919 and 0.9399, respectively, when the Gaussian noise is 15 dB, 25 dB and 35 dB, respectively, in the thin section image of the small-pore and fine-throat-type structures of J Oilfield; however, the data become 27.2841 and 0.9228, 26.8177 and 0.9162, and 26.3043 and 0.9068 for CBM3D, respectively, and these data generated by other methods are between the aforementioned two sets of data. The normalized root mean squared error (NRMSE) generated by the GR-GAN and CBM3D with the test set are 0.0327 and 0.1382, 0.0584 and 0.1341, and 0.0786 and 0.1382, respectively, when the Gaussian noise is 15 dB, 25 dB and 35 dB, respectively, and the NRMSE generated by the other methods is also between the aforementioned two sets of data. For other types of thin section images, when the Gaussian noise is 15 dB, 25 dB and 35 dB, respectively, CBM3D, K-SVD, the GAN, FFDNet and the GR-GAN show similar denoising effects as previously described. Moreover, in a denoising experiment repeated more than 10 times with the above methods, the GR-GAN has the shortest mean running time of 1.0589 s, and the mean running times of CBM3D, K-SVD, the GAN and FFDNet are 6.4609 s, 155.3158 s, 1.9394 s and 1.0622 s, respectively.
Wellbore leakage is complicated to understand due to the range of potential leakage pathways and uncertainties regarding their capacities. In this study we present a novel approach to modelling realistic leakage along microannulus pathways of varying thickness. We use stochastic methods to calibrate leakage pathway dimensions to the surface casing vent flow (SCVF) leakage rates reported in British Columbia, Canada. Results shows that representing dry microannulus thicknesses with a lognormal distribution provides a good fit for the intermediate ranges of SVCF flow rates, but that a dry microannulus alone cannot account for all instances of wellbore leakage. We then approach small and high flow rates independently, offering explanations for these. This includes a wet microannulus/mud channel model to account for instances of poor mud removal, which is better able to account for the less frequent higher leakage rates. We conclude that flow rates above 10 m/day are progressively likely to be caused by significant failures in mud displacement during primary cementing, or other extreme events such as casing failure due to geological or operational factors.
Supercritical carbon dioxide (ScCO2) drilling can effectively protect shale formation from hydration damage and improve drilling rate comparing to conventional drilling technology. The wellbore stability of shale formation is one considerable issue under ScCO2 drilling conditions. In this study, the numerical simulations are performed to calculate collapse cycling time of shale formation under ScCO2 drilling conditions based on thermoporoelastic coupling model. The results show that comparing to water seepage condition, the variation of formation temperature is larger, pore pressure and stress are lower for ScCO2 seepage condition without adsorption effect, the comparison between water and ScCO2 seepage conditions verifies the thermoporoelastic coupling model. For ScCO2 drilling conditions, if adsorption‒induced strain is ignored, the risk of wellbore collapse will be slightly underestimated comparing to the results with adsorption effect. When adsorption‒enhanced elastic modulus is ignored, the risk of wellbore collapse will be significantly underestimated comparing to the results with adsorption effect. The wellbore collapse may occur with the increasing well depth for ScCO2 drilling conditions. This study can provide the theoretical guidance for exploiting shale reservoirs using ScCO2.
Recently, the petroleum industry has focused on deeply buried reservoir discoveries and exploring potential CO2 storage sites close to existing infrastructure to increase the life span of already operating installations to save time and cost. It is therefore essential for the petroleum industry to find an innovative approach that exploits the existing core- and well log data to be successful in their endeavor of effectively characterizing and predicting reservoir quality. Continuous data sources (e.g. wireline logs) have a huge potential compared with expensive, time inefficient and sporadic data from cores in determining reservoir quality for use in a regional context. However, whereas core analysis offers in-depth knowledge about rock properties and diagenetic processes, continuous data sources can be difficult to interpret without a formation-specific framework. Here, we demonstrated how the pre-existing core data could be effectively used by integrating petrographic- and facies data with a pure predictive machine learning (ML) based porosity predictor. The inclusion of detailed core analysis is important for determining which reservoir parameter(s) that should be modeled and for the interpretation of model outputs. By applying this methodology, a framework for deducing lithological and diagenetic attributes can be established to aid reservoir quality delineation from wireline logs that can be used in frontier areas. With the ML porosity model, a Random Forest Regressor, the square of the correlation was 0.84 between predicted- and helium porosity test data over a large dataset consisting of 38 wells within the Stø Formation across the SW Barents Sea. By integrating the continuous ML porosity logs and core data, it was possible to differentiate three distinct bed types on wireline log responses within the Stø Formation. Particularly, the relationship between Gamma ray (GR) and porosity was effective in separating high porosity clean sand-, low porosity cemented clean sand and more clay and silt rich intervals. Additionally, in the P-wave velocity (VP) - density domain, separation of high porosity clean sand- and heavily cemented low porosity clean sand intervals were possible. The results also show that the ML derived porosity curves coincide with previously published and independent facies data from a selection of the wells included in the study. This demonstrates the applicability of the model in the region, because the Stø Formation has been described to exhibit similar lithological- and mineralogical properties over large parts of the Western Barents Sea area. Even though, continuous porosity data could be estimated from other sources like VP, neutron or density logs, this would generally require matrix and fluid information. This study demonstrated the effectiveness of the ML model in generating continuous porosity logs that are useful for characterizing and predicting reservoir properties in new wells. This methodology
Tuning the concentration of the ions is beneficial for improving oil recovery by water flooding. Despite the widely recognized distribution of salt ions at the water interface, their effects on the structure of interfacial water, such as hydrogen(H) bonds, are unclear. In this study, using oblique incident reflectance difference (OIRD) technique and interfacial rheometer to analyze the alkanes-ion solution interface, we show that ions have a significant effect on the perturbation of hydrogen bonds at the alkanes-water interface. The change in the water layer structure follows the gradual increase in the concentration of Na2SO4/Na2CO3 and the decrease in the interfacial tension, and dielectric constant at the alkane-solution interface. Specifically, structure-breaking anions such as SO42− and CO32− decrease the average H-bonding of water at the alkane/water interface, thus damaging the molecular cluster structure at the interface. Although Cl− will form hydration ions with water molecules, it will not break the hydrogen bond structure between water molecules at the interface. These results indicate the mechanism of anion effects on the alkane/water interface, and for samples with high saturated alkane content, a repellent solution containing SO42− can be preferentially selected for repelling, providing a new idea for the study of the molecular boundary of the oil-water interface.
Treatment of the oilfield wastewater from the chemical and petroleum industries, often present in the form of emulsion, is one of the major environmental concern in current times. Demulsification is presently the most viable method to separate the oil and water from a rigid, homogenous emulsion especially, chemical demulsification. Mostly, chemical demulsifiers used at high temperature can give enhanced separation efficiency and result in the use of less dosage of expensive chemicals. Mainly, the reservoir conditions also exist at high temperature, thus, it is important to consider the effect of temperature for the selection of best choice among available demulsifiers. The review discusses the recent discoveries and modification among the existing demulsifiers such as triblock EO-PO copolymer, non-biodegradable polymers, branched copolymers and others. The major chemical demulsifiers and their upcoming alternatives such as the nanomaterial demulsifiers and ionic liquids have also been discussed in great details. Chemical structure and molecular weight were found to influence the emulsion breaking ability of a demulsifier. The surface properties play an important role in the selection of appropriate demulsifier whether hydrophobic or hydrophilic. Method of heating whether microwave or conventional heating, doesn't play a significant role in influencing the emulsion breaking efficiency of polymeric surfactants. However, microwave heating is preferred for demulsification by ionic liquids. Lastly, the whole mechanism of chemical demulsification and few upcoming chemical treatments for demulsification are also well described in brief.
Considering the complex factors controlling volcanic reservoirs, the Carboniferous strata in the eastern slope area of the Mahu Sag (ESMS) in the northwestern Junggar Basin (NJB) were investigated using rock cores, thin sections, scanning electron microscope (SEM), physical properties, major elements, X-ray fluorescence (XRF), well logging, and seismic data. The volcanic rocks revealed by drilling are mostly weathering crust reservoirs (WCRs), the formation of which in and around the study area is significantly controlled by weathering and leaching (WL). Most types of volcanic rock can be improved by long-term weathering. Favorable reservoirs in the ESMS are often developed within 150 m below the tectonic unconformity boundary at the top of the Carboniferous. The longer the weathering duration, the better are the overall quality of the WCRs. Weathering duration of about 40 Ma is probably an important threshold in the NJB. Ultra-long leaching of atmospheric water and strong late dissolution of acidic fluids before oil and gas accumulations are important for reservoir development and petroleum accumulation in volcanic strata filled with authigenic minerals, especially calcite. The early regional tectonic movement affected the volcanic eruption and controlled the lithofacies distribution. The linear density of fractures was negatively correlated with the distance from the main controlling fault. Owing to the relatively weak filling, high-angle fractures contribute significantly to the reservoir permeability. The physical properties of volcanic breccia are better than those of tuff, and the porosity, permeability, and fracture density of andesite are higher than those of basalt. The physical properties of near-source facies belts of a volcanic edifice are better than those of far-source facies ones. Favorable exploration areas are the structural highs and fault zones where the duration of WL is more than 40 Ma, explosive facies and effusive facies near the crater are developed, or the inherited ancient buried hills transformed by faults and fractures near excellent source rocks, where the dissolution of atmospheric water and organic acidic fluids are strong.
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