Synthesizing Nuclear Magnetic Resonance (NMR) Outputs for Clastic Rocks Using Machine Learning Methods, Examples from North West Shelf and Perth Basin, Western Australia

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.

Subsurface Investigation Using Electrical Resistivity Imaging for Proposed Industrial Site near Erbil-Kirkuk Borders, Northern Iraq

The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel profiles in a specific direction. The positions of Electrical Resistivity Imaging profiles in the project area have been determined according to a preliminary subject plan from the civil engineers for factory foundation constructions and proposed locations of heavy machines. The inversion results of profiles showed that areas of blocks A, B, C, and D consist mainly of clastic rocks and sediments, e.g., claystone, siltstone and sandstone. The Electrical Resistivity Imaging inversion sections of blocks A, B, C, and D do not show any indication of cavitation or weak zones of sizes more than 2.0 meters, and no signs of gypsum bodies are found in these areas in general. Gypsum bodies are probably detected at block E, the southern part of the study area. The researchers recommended to keep these rocks in block E away from the continuous running water to avoid cavitation. Furthermore, the construction of heavy machines should keep away from this part of the study area to avoid to some extent, subsoil failure and subsidence in the future. Middle and Northern parts are more consistent to the constructions and factory foundations.

Integrated 3D Mechanical Earth Modelling to Intensively Investigate the Wellbore Instability of Zubair Oil Field, Southern Iraq

Wellbore instability in the Zubair oil field is the main problem in drilling operations. This instability of the wellbore causes several problems including poor hole cleaning, tight hole, stuck pipe, lost circulation, bad cementing, and well kick or blowout that lead to an increase in the nonproductive time. This article aims to set up an appropriate drilling plan that mitigates these instability issues for further well drilling. Field data from six wells (logs, drilling and geological reports as well as offset well tests) were used to build a one-dimensional mechanical earth modeling for each well. The constructed model of selected wells was combined to construct the three-dimensional mechanical earth modeling, which can enable the distribution of all estimated geomechanical parameters along the field of interest. The results revealed that the strip slip and normal faults are the common fault regimes in Zubair oil field located in carbonate rocks and clastic rocks, respectively. The Mogi-Coulomb failure criterion is conservative in determining the minimum and maximum mud weight, and it agrees with the determination of real failure from the image/and caliper logs. The best direction to drill the deviated and horizontal wells was towards the minimum horizontal stress with 140o azimuth from the north. The recommended ranges of mud weight along the sections of 12.25" and 8.5" of the highly deviated and horizontal wells were (between 1.46 and 1.58 gm/cm3) without any expected wellbore instability problems. Based on the outcomes of 3D model, it is expected that the wellbore instability issues are most likely to occur in the domes of; Shauiba and Hamma and in formations; Tanuma, Khasib and Nahr-Umr. In contrast the less wellbore instability problems are expected to expose in Rafidya dome. The study presents an appropriate mud window that can be used to design to minimize the wellbore stability problems when new wells will be drilled in Zubair oil field.

Machine Learning Guided 3D Image Recognition for Carbonate Pore and Mineral Volumes Determination

<p>Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and can deal with a massive amount of data and images seamlessly. Geoscientists and petroleum engineers face difficulties in setting the direction of the optimum method for determining petrophysical properties from core plug images of optical thin-sections, Micro-Computed Tomography (μCT), or Magnetic Resonance Imaging (MRI). Most of the successful work is from the homogeneous and clastic rocks focusing on 2D images with less focus on 3D and requiring numerical simulation. Currently, image analysis methods converge to three approaches: image processing, artificial intelligence, and combined image processing with artificial intelligence. In this work, we propose two methods to determine the porosity from 3D μCT and MRI images: an image processing method with Image Resolution Optimized Gaussian Algorithm (IROGA); advanced image recognition method enabled by Machine Learning Difference of Gaussian Random Forest (MLDGRF).</p><p>Meanwhile, we have built reference 3D micro models and collected images for calibration of the IROGA and MLDGRF methods. To evaluate the predictive capability of these calibrated approaches, we ran them on 3D μCT and MRI images of natural heterogeneous carbonate rock. We also measured the porosity and lithology of the carbonate rock using three and two industry-standard ways, respectively, as reference values. Notably, IROGA and MLDGRF have produced porosity results with an accuracy of 96.2% and 97.1% on the training set and 91.7% and 94.4% on blind test validation, respectively, in comparison with the three experimental measurements. We measured limestone and pyrite reference values using two methods, X-ray powder diffraction, and grain density measurements. MLDGRF has produced lithology (limestone and pyrite) volume fractions with an accuracy of 97.7% in comparison to reference measurements.</p>

Machine Learning Guided 3D Image Recognition for Carbonate Pore and Mineral Volumes Determination

<p>Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and can deal with a massive amount of data and images seamlessly. Geoscientists and petroleum engineers face difficulties in setting the direction of the optimum method for determining petrophysical properties from core plug images of optical thin-sections, Micro-Computed Tomography (μCT), or Magnetic Resonance Imaging (MRI). Most of the successful work is from the homogeneous and clastic rocks focusing on 2D images with less focus on 3D and requiring numerical simulation. Currently, image analysis methods converge to three approaches: image processing, artificial intelligence, and combined image processing with artificial intelligence. In this work, we propose two methods to determine the porosity from 3D μCT and MRI images: an image processing method with Image Resolution Optimized Gaussian Algorithm (IROGA); advanced image recognition method enabled by Machine Learning Difference of Gaussian Random Forest (MLDGRF).</p><p>Meanwhile, we have built reference 3D micro models and collected images for calibration of the IROGA and MLDGRF methods. To evaluate the predictive capability of these calibrated approaches, we ran them on 3D μCT and MRI images of natural heterogeneous carbonate rock. We also measured the porosity and lithology of the carbonate rock using three and two industry-standard ways, respectively, as reference values. Notably, IROGA and MLDGRF have produced porosity results with an accuracy of 96.2% and 97.1% on the training set and 91.7% and 94.4% on blind test validation, respectively, in comparison with the three experimental measurements. We measured limestone and pyrite reference values using two methods, X-ray powder diffraction, and grain density measurements. MLDGRF has produced lithology (limestone and pyrite) volume fractions with an accuracy of 97.7% in comparison to reference measurements.</p>

Constraining the timing of Arabia-Eurasia collision in the Zagros orogen by sandstone provenance (Neyriz, Iran)

The Zagros orogen, formed by the collision of the Arabian and Eurasian continental margins, represents one of the largest and richest oil and gas provinces in the world. The Zagros fold-thrust belt records collision and convergence along the Neotethys suture zone. By coupling field observations, sandstone modal analysis, U-Pb zircon dating, and Hf isotopic data from the Upper Cretaceous to Pliocene sedimentary succession of the Neyriz region, this paper documents several major provenance changes that allow us to propose a refined scenario for the Zagros orogeny. An ophiolitic complex dated by detrital-zircon U-Pb geochronology as ca. 95 Ma provided detritus to Upper Cretaceous-Paleocene strata deposited along the northeastern margin of the Arabian lower plate (ophiolite provenance). Yet, on the southwestern margin of the Eurasian upper plate, upper Paleocene-lower Eocene strata indicate provenance from Mesozoic magmatic rocks yielding zircons dated as ca. 240 Ma and 170 Ma as well as the recycling of clastic rocks. Since the early Miocene, the sedimentary basin located on the Arabian plate received both ophiolitic detritus and magmatic-arc, recycled clastic, and axial-belt metamorphic detritus from Eurasia. U-Pb ages of detrital zircons reflect polyphase magmatism at 170 Ma, 95 Ma, and 40 Ma on the Eurasian active margin. Our results indicate that progressive accretion, uplift, and exhumation of the Zagros orogen was well under way by the beginning of the Miocene in the Neyriz region. Literature data from adjacent regions suggest that the Arabia/Eurasia collision may have occurred diachronously and later in the Kermanshah and Lurestan areas to the north.

Effects of Water on Natural Stone in the Built Environment—A Review

The present work reviews studies with information on the effects of water by itself on stones of the built environment both to assess the impact of this substance and to discuss possible implications for conservation. The analysis concerns empirical results from previous publications dealing with the effects, on several rock types, of freeze–thaw, wetting, erosion by running water and substances resulting from the water–stone interaction. Laboratory studies have shown that water freezing can cause physical damage even in low porosity rocks. As far as we know, this is the first review that considers comparative laboratory studies of freeze–thaw and salt crystallization on the same rock specimens, and these point to lower erosive effects than salt weathering, as freeze–thaw can provoke catastrophic cracking. Wetting has shown strong damaging effects on some fine-grained clastic rocks. Erosive features have been reported for rain exposition and for some fountain settings albeit, in these field studies, it could be difficult to assess the contribution of pollutants transported by water (this assessment could have meaningful implications for stone conservation, especially in fountain settings). Water also interacts with stone constituents, namely sulfides and soluble salts, releasing substances that could impact those stones. Sulfides are a relatively frequent issue for slates and granites, and our observations suggest that for this last rock type, this issue is mostly associated with the presence of enclaves and, hence, avoiding the surface exposition of such enclaves could solve the problem.

Geochemistry of the Paleocene Clastic Rocks From the Southwestern Jianghan Basin, Central China Reveal Their Provenance, Tectonic Setting, and Palaeoenvironment

This paper intends to learn about the provenance, tectonic setting and paleoenvironment of the Paleocene Shashi Formation in the southern Jianghan Basin by the bulk-rock geochemistry. The K2O/Al2O3 and SiO2/Al2O3 ratios indicate that the major proportion of samples are litharenite. The chondrite-normalized REE distribution pattern of the Shashi Formation’s mudstones are characterized by enriched LREE and flat HREE similar to those of UC with negative Eu anomalies. Combined with the geochemical element ratio discriminant diagram, such as Al2O3-TiO2, Zr-TiO2, La/Sc-Co/Th, and Hf-La/Th, so on, these samples were sourced from mixed felsic/basic rock. Moreover, the discriminant diagrams of K2O/Na2O-SiO2/Al2O3, La-Th-Sc, and Th-Co-Zr/10 suggest that the samples were formed under the tectonic settings of active continental margin and continental island arc. The values of CIA, CIW, PIA, ICV, Zr/Sc-Th/Sc, and ternary diagrams of A-(CN)-K and Al2O3-Zr-TiO2 indicate that weathering in the source area was weak and source rocks have not been reformed by depositional recirculation and hydraulic sorting. And the palaeoenvironmental indicators of C-value, Ni/Co, V/Cr, V/(V+Ni) and Sr/Cu, Ga/Rb indicate that the climate was cool and arid during the evaporite deposition period in the southern Jianghan Basin, and the water was in the condition of oxidation.

Geochemistry and Petrography of the Sediments From the Marginal Areas of Qinghai Lake, Northern Tibet Plateau, China: Implications for Weathering and Provenance

The provenance study of the sediments from Qinghai Lake is of great significance for the understanding of geological and climatic evolution processes of the Tibet Plateau on the one hand and for evaluating the controlling factors of the sediment components on the other hand. The samples were collected from five rivers, foreshore, beach, beach bar, and aeolian sand dune in the Qinghai Lake. The bulk geochemical composition, petrography, and mineralogy features of the samples are analyzed. The results show that: 1) Qinghai Lake sediments experienced low-intensity chemical weathering from the source areas to the deposition sites and were affected by some recycled detrital materials and 2) the source rocks for the sediments include felsic rocks (granite, granodiorite, and felsic volcanic rocks), carbonate, metamorphic rocks (marble and meta-volcanic rocks), and clastic rocks with the felsic source rocks to have the most important impact on the chemical compositions of the sediments. The geochemical indicator of Al2O3/TiO2 reflects that the provenance of fine-grained sediments from the center of Qinghai Lake is more mafic than the coarse-grained sediments from the margin of the Qinghai Lake, suggesting that the hydraulic sorting of grain size probably plays an important role in the geochemical compositions of the sediments. The mafic elements were probably preferentially enriched in muds.