Geodynamic conditions of massive sulfide formation in the Magnitogorsk megazone

Research subject. Volcanism, rock geochemistry, geodynamics, and massive sulfide formation in the Magnitogorsk megazone (MMZ) of the Southern Urals in the Middle Paleozoic.Materials and Methods. Across the largest part of the massive sulfide deposits under investigation, the authors conducted route studies, including geological surveys of individual ore fields and quarries of deposits, core samples of deep wells and transparent sections. Representative analyses of petrogenic and microelements were performed using wet chemistry and ICP-MS in analytical centers in Russia and Europe. Along with the authors’ data, analytical materials published by Russian and foreign researchers were used. Geodynamic reconstructions were carried out taking into account regional data on gravics, thermal field, magnetometry, and seismic stu dies, including «Urseis-95».Results. The geodynamic reconstructions established that the main elements of the paleostructure of the Southern Urals in the Devonian were the subduction zone of the eastern dip and asthenospheric diapirs that penetrated into the «slab-window», which determined the type of volcanic belts, the composition and volume of volcanic rocks of pyrite-bearing complexes, and ore matter of pyrite deposits. The following geodynamic zones in the MMZ were identified: 1 – polychronous accretion prism; 2 – frontal and developed island arcs (D1e2–D2ef1); 3 – zone of back-arc spreading (D1e2); 4 – rear island arc (D2ef1).Conclusions. All investigated zones and ore areas are characterized by an autonomous development of volcanism, a special deep structure and a different composition, as well as by a different volume of massive sulfide deposits that vary in the Cu and Zn ratios and Pb, Ba, Au amounts. In the MMZ volcanic complexes, three groups of plume source basalts are distinguished. The results can be used in predictive-estimation and search operations for massive sulfide mineralization.

Transformer-Based Deep Learning Models for Well Log Processing and Quality Control by Modelling Global Dependence of the Complex Sequences

A single well from any mature field produces approximately 1.7 million Measurement While Drilling (MWD) data points. We either use cross-correlation and covariance measurement, or Long Short-Term Memory (LSTM) based Deep Learning algorithms to diagnose long sequences of extremely noisy data. LSTM's context size of 200 tokens barely accounts for the entire depth. Proposed work develops application of Transformer-based Deep Learning algorithm to diagnose and predict events in complex sequences of well-log data. Sequential models learn geological patterns and petrophysical trends to detect events across depths of well-log data. However, vanishing gradients, exploding gradients and the limits of convolutional filters, limit the diagnosis of ultra-deep wells in complex subsurface information. Vast number of operations required to detect events between two subsurface points at large separation limits them. Transformers-based Models (TbMs) rely on non-sequential modelling that uses self-attention to relate information from different positions in the sequence of well-log, allowing to create an end-to-end, non-sequential, parallel memory network. We use approximately 21 million data points from 21 wells of Volve for the experiment. LSTMs, in addition to auto-regression (AR), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) conventionally models the events in the time-series well-logs. However, complex global dependencies to detect events in heterogeneous subsurface are challenging for these sequence models. In the presented work we begin with one meter depth of data from Volve, an oil-field in the North Sea, and then proceed up to 1000 meters. Initially LSTMs and ARIMA models were acceptable, as depth increased beyond a few 100 meters their diagnosis started underperforming and a new methodology was required. TbMs have already outperformed several models in large sequences modelling for natural language processing tasks, thus they are very promising to model well-log data with very large depth separation. We scale features and labels according to the maximum and minimum value present in the training dataset and then use the sliding window to get training and evaluation data pairs from well-logs. Additional subsurface features were able to encode some information in the conventional sequential models, but the result did not compare significantly with the TbMs. TbMs achieved Root Mean Square Error of 0.27 on scale of (0-1) while diagnosing the depth up to 5000 meters. This is the first paper to show successful application of Transformer-based deep learning models for well-log diagnosis. Presented model uses a self-attention mechanism to learn complex dependencies and non-linear events from the well-log data. Moreover, the experimental setting discussed in the paper will act as a generalized framework for data from ultra-deep wells and their extremely heterogeneous subsurface environment.

Digging Deeper: Deep Wells, Bore-Wells and Water Tankers in Peri-Urban Hyderabad

Hyderabad in India is a rapidly growing city and a popular global hub of high-tech and information technology industries. With its aspiration to be a global destination for transnational companies and engine of economic growth for the twenty-first century, it is rapidly urbanizing and expanding outward with intense infrastructure development. With this rapid expansion, the city increasingly witnesses water insecurity, especially in its peri-urban areas. To supply the high-tech and aspirational pockets of Hyderabad, water has been piped and sourced from far-away reservoirs, deep wells, and borewells, as well as through water tankers that collected water from the surrounding peri-urban areas. These unsustainable practices have led to groundwater shortages and severe water insecurity for the ordinary residents living at the edge of the city. Through a grounded understanding based on ethnographic fieldwork, this chapter delves into the everyday experiences of water insecurity in peri-urban Hyderabad. The chapter discusses the context of vulnerability and ways of coping in relation to water insecurity in peri-urban communities. It seeks to give a micro- and nuanced view of rural-urban relationships around water in Hyderabad, in a context of water-related conflicts, privatization and (piped) connections between the urban and peri-urban localities.

Study on the Rheological Properties of Ultra-High Temperature CGA Drilling Fluids

Colloidal gas aphron (CGA) drilling fluids are a kind of environmentally-friendly underbalanced drilling technique, which has attracted more attention in depleted reservoirs and other low-pressure areas. With the shortage of global oil/gas resources, drilling has gradually shifted to high-temperature and deep wells. Hence, a study on the ultra-high temperature rheology properties of CGA fluids is lacking and urgently needed. In this study, a novel CGA drilling fluid system was prepared by modified starch and amino acid surfactant, and rheological properties after 120-300°C aged was investigate. Results show that: (1) Herschel-Bulkley model is the preferred model to predict CGA drilling fluid at ultra-high temperatures; (2) It was proved that CGA drilling fluid is a high-quality drilling fluid with extremely high value of LSRV and shear thinning property within 280°C. Compared to the traditional XG-based CGA drilling fluid, the improvement of LSRV at ultra-high temperatures is a significant advantage of EST-based CGA drilling fluid which is conducive to carrying cuttings and sealing formation pores.

On the circulation of hydrogen in the atmosphere and the Earth’s crust

A review of data on sources and sinks of hydrogen of various origins in the atmosphere and in the near-surface part of the Earth’s crust is given (only some cases we are talking about the crust as a whole). Based on the results of the consideration of this information, it was concluded that the influence of underground non-biogenic («geological») hydrogen on the content and balance of gas in the atmosphere, up to the stratosphere, is insignificant. The complexity of the experimental determination of the flow of geological hydrogen, free of biogenic and anthropogenic interference, the influence of the testable excavation, etc. is obvious. Probable sources of deep hydrogen are considered: the remains of magmatic gases (outside the areas of volcanism), metamorphic reactions, and radiolysis of water. The potential for significant H2 flow is only apparent in areas of currently activated faults. The data on the most powerful suppliers of geological hydrogen — modern active volcanoes and thermal fields are given. The gas circulation scheme of the Avachinsky volcano is built, based on the thermal model. The latter is controlled by data from geothermometers, the results of direct temperature measurements in deep wells, and a velocity model. The possibility of fumaroles carrying unchanged hydrogen from the magma chamber has been shown. The prospects for the formation of hydrogen deposits are estimated as uncertain. Magmatic and metamorphogenic gas in some areas is formed enough to accumulate a significant deposit over several tens of thousands of years. But the possibility of its preservation during this period or longer raises doubts. Hydrocarbon deposits without material input from great depths can lose reserves in much less time. Higher rocks permeability to hydrogen contributes to much greater gas leakage.

Design and Evaluation of High-Temperature Well Cementing Slurry System Based on Fractal Theory

The efficient development of oil and gas resources is inseparable from the progress of drilling technology and the safety of the long life cycle of wellbore. At present, exploration and development is expanding to deep and ultra-deep areas. The long life cycle safety of deep and ultra-deep wells is mainly realized by the sealing performance of cement slurry. Additionally, the accumulation degree of cement slurry particles is closely related to sealing performance. Based on fractal theory, an accumulation model of continuous distribution of additive material particles was designed, which can determine the range of fractal dimension necessary to realize the tight stacking and guide the proportion of solid admixture. The formulation of high temperature-resistant cement slurry was prepared by designing the ratio of solid admixture and optimizing the high temperature-resistant liquid admixture. The evaluation of engineering and temperature resistance of the cement slurry proves the rationality of the accumulation model, which can be applied to the design of a high temperature cementing slurry system in deep and ultra-deep wells.

The effect of land subsidence on the selection of raw water sources in hotel and apartment buildings in Semarang city

The Semarang City Government prohibits groundwater/deep wells in hotel and apartment buildings because the use of groundwater or deep wells in locations that have experienced subsidence will further aggravate the subsidence. The method used in this research is to purposively select hotel and apartment buildings in Semarang that have received an assessment by the Semarang City Building Expert Team and have received a certificate of serviceability. Furthermore, compare the map of land subsidence in some areas of the city of Semarang with the natural water sources used by the hotel and apartment buildings. The research results showed that from 10 hotel and apartment buildings, there were 7 that used deep wells in zone level II, namely subsidence between 2.1 to 4 cm/year. Meanwhile, 3 other hotel and apartment buildings use water from the Municipal Drinking Water Company of Semarang. The existence of hotel and apartment buildings that use groundwater/deep wells in zone level II will increase and trigger the more significant subsidence in the area, thereby increasing the level of subsidence to level III.

Force Analysis of Logging Cable in Deep Well

With the increase of deep wells, high temperature and high pressure wells and complex wells, the demand for logging is also increasing. Wireline logging is an important technical means to obtain downhole data in the process of petroleum testing. This paper establishes a cable mechanics model by analyzing the main influencing factors of the cable force in the inclined well section or the vertical well section. Calculate the lifting power of the tool. Through logging calculation, the force change law of the downhole cable and tool string is obtained when the wellhead pressure changes.

Analysis of Development Status of High Performance Water-based Drilling Fluid

Deep wells, ultra deep wells and unconventional oil and gas exploitation have gradually become the focus of exploration and development. The oil-based drilling fluid is gradually replaced by water-based drilling fluid because of the impact of cost and environmental protection factors. In order to better replace oil-based drilling fluid, research on high-performance water-based drilling fluid has been carried out at home and abroad, and its comprehensive performance has gradually approached that of oil-based drilling fluid. The research progress and future development trend of high performance water-based drilling fluid abroad are introduced.