Induced microearthquakes predict permeability creation in the brittle crust

Fracturing controls rates of mass, chemical and energy cycling within the crust. We use observed locations and magnitudes of microearthquakes (MEQs) to illuminate the evolving architecture of fractures reactivated and created in the otherwise opaque subsurface. We quantitatively link seismic moments of laboratory MEQs to the creation of porosity and permeability at field scale. MEQ magnitudes scale to the slipping patch size of remanent fractures reactivated in shear - with scale-invariant roughnesses defining permeability evolution across nine decades of spatial volumes – from centimeter to decameter scale. This physics-inspired seismicity-permeability linkage enables hybrid machine learning (ML) to constrain in-situ permeability evolution at verifiable field-scales (~10 m). The ML model is trained on early injection and MEQ data to predict the dynamic evolution of permeability from MEQ magnitudes and locations, alone. The resulting permeability maps define and quantify flow paths verified against ground truths of permeability.

Estimation of the Squirt-Flow Length Based on Crack Properties in Tight Sandstones

Tight sandstones have low porosity and permeability and strong heterogeneities with microcracks, resulting in small wave impedance contrasts with the surrounding rock and weak fluid-induced seismic effects, which make the seismic characterization for fluid detection and identification difficult. For this purpose, we propose a reformulated modified frame squirt-flow (MFS) model to describe wave attenuation and velocity dispersion. The squirt-flow length (R) is an important parameter of the model, and, at present, no direct method has been reported to determine it. We obtain the crack properties and R based on the DZ (David-Zimmerman) model and MFS model, and how these properties affect the wave propagation, considering ultrasonic experimental data of the Sichuan Basin. The new model can be useful in practical applications related to exploration areas.

Semi-Supervised Learning–Based Petrophysical Facies Division and “Sweet Spot” Identification of Low-Permeability Sandstone Reservoir

The identification of the “sweet spot” of low-permeability sandstone reservoirs is a basic research topic in the exploration and development of oil and gas fields. Lithology identification, reservoir classification based on the pore structure and physical properties, and petrophysical facies classification are common methods for low-permeability reservoir classification, but their classification effect needs to be improved. The low-permeability reservoir is characterized by low rock physical properties, small porosity and permeability distribution range, and strong heterogeneity between layers. The seepage capacity and productivity of the reservoir vary considerably. Moreover, the logging response characteristics and resistivity value are similar for low-permeability reservoirs. In addition to physical properties and oil bearing, they are also affected by factors such as complex lithology, pore structure, and other factors, making it difficult for division of reservoir petrophysical facies and “sweet spot” identification. In this study, the logging values between low-porosity and -permeability reservoirs in the Paleozoic Es3 reservoir in the M field of the Bohai Sea, and between natural gamma rays and triple porosity reservoirs are similar. Resistivity is strongly influenced by physical properties, oil content, pore structure, and clay content, and the productivity difference is obvious. In order to improve the identification accuracy of “sweet spot,” a semi-supervised learning model for petrophysical facies division is proposed. The influence of lithology and physical properties on resistivity was removed by using an artificial neural network to predict resistivity R0 saturated with pure water. Based on the logging data, the automatic clustering MRGC algorithm was used to optimize the sensitive parameters and divide the logging facies to establish the unsupervised clustering model. Then using the divided results of mercury injection data, core cast thin layers, and logging faces, the characteristics of diagenetic types, pore structure, and logging response were integrated to identify rock petrophysical facies and establish a supervised identification model. A semi-supervised learning model based on the combination of “unsupervised supervised” was extended to the whole region training prediction for “sweet spot” identification, and the prediction results of the model were in good agreement with the actual results.

Pumping test analysis for assessment of hydraulic parameters and aquifer system formation in hilly terrain

Groundwater conditions (GWCs) of an area depends on aquifer hydraulic parameters such as storativity () or storage coefficient (), transmissivity () and hydraulic conductivity (). It plays a key role concerning- groundwater flow modeling, well performance, solute and contaminants transports assessment and also for identification of areas for additional hydrologic testing. Specifically, the geologic formation of a regions control the porosity and permeability, however, in hilly terrain prospecting ground water potential is more challenging due to its limited extent and its occurrences that are usually confined to fractures and weathered rocks. The present study, aims at estimating the hydraulic parameters through pumping test analysis to assess aquifer system formation on hilly terrain from 16 bore wells. The aforesaid parameters were examined through a case study in some selective regions of Hamirpur district of Himachal Pradesh, India. The study area is controlled under two main geological horizons that is the post-tertiary and tertiary. The papers end with comparative results of hydraulic parameters and the aquifers system formation on different GWCs which may be helpful in the outlook of sustainable groundwater resource in the regions.

Characteristics and influencing factors of Cretaceous reservoir in eastern depression of North Yellow Sea basin

Cretaceous is the key exploration target layer in the eastern depression of North Yellow Sea basin, which has a good prospect for oil and gas exploration. Its huge oil and gas resource potential has attracted great attention from petroleum geologists. In this study, the main rock types, reservoir space types, petrophysical characteristics and main controlling factors of Cretaceous reservoir are studied through core observation, thin section identification, petrophysical analysis and scanning electron microscope observation. The results indicate that the main rock types of Cretaceous reservoir in the eastern depression of North Yellow Sea basin are lithic arkose, feldspar lithic sandstone, some feldspar sandstone and a small amount of lithic sandstone. The average porosity is 6.9%, and the average permeability is 0.46 × 10−3 μm, so Cretaceous reservoir in the study area has poor petrophysical characteristics and belongs to low porosity and low permeability reservoir. Cretaceous reservoirs in the study area mainly develop in secondary pores, which are dominated by dissolution pores (including intragranular pores, intercrystalline pores and cleavage pores), followed by fractures. The main factors affecting petrophysical characteristics of Cretaceous reservoir in the study area are provenance properties, sedimentation, diagenesis (including compaction, cementation and dissolution) and tectonism. The provenance properties and sedimentation are the prerequisite conditions affecting petrophysical characteristics. Petrophysical characteristics of feldspar sandstone of Cretaceous reservoir in the study area and lithic arkose are better than that of feldspar lithic sandstone. Both compaction and cementation reduce the porosity and permeability of Cretaceous reservoir in the study area and make petrophysical characteristics become poor, whereas the dissolution and tectonism play an important role in improving petrophysical characteristics of Cretaceous reservoir.

Evaluation of copper tailings from the abandoned Messina Mine for possible reuse in recreational projects, South Africa

Historic mining of copper around Musina Town left behind a sizeable unrehabilitated tailing dump. This article reports on the study conducted to investigate the suitability of using copper tailings as sand replacement in recreational projects. The methodology used involved analyzing the particle size distribution and plasticity index (PI) of the tailings and determining their particle density, bulk density, particle shape, total porosity, and permeability coefficient. The pH of the tailings, major element oxides, and heavy metals composition were all analyzed. The tailings were classified as poorly graded sand with silt (SP-SM). Low fines (9.6%) and PI (1.4) values revealed that the copper tailings were texturally suitable for application in rootzones of sports fields, courts for beach volleyball, and bunkers of the golf courses. Their particle density (2.90 g/cm³), bulk density (1.53-1.89 g/cm³), porosity (34.62-47.04%), and permeability (1.42 x 10-3 cm/sec) were all within the recommended range for application in rootzones. The angular particles of the tailings supported their uses in the bunkers. However, their pH (7.9) and high quartz content (69% SiO2) confirmed their suitability for rootzones. However, the high concentration of Cu (1872.0 mg/kg) and Cr (159.5 mg/kg) was identified as a potential risk of using the copper tailings in rootzones. This and the relatively high Al2O3 (11%) and Fe2O3 (8%) suggested that the copper tailings should be first washed or processed before being used in any recreational projects. Developing a suitable technique for processing the studied copper tailings to enhance their properties for different recreational projects was recommended.

Relationship between pore throat and permeability of porous carbonate reservoir in the Middle East

A significant behavior of carbonate reservoirs is poor correlation between porosity and permeability. With the same porosity, the permeability can vary by three orders of magnitude or more. An accurate estimation of permeability for carbonate reservoir has been a challenge for many years. The aim of this study was to establish relationships between pore throat, porosity, and permeability. This study indicates that pore throat radius corresponding to a mercury saturation of 20% (R20) is the best permeability predictor for carbonates with complex porous pore networks. Quantitative analysis was made to achieve three different patterns of pore throat for 417 carbonate samples which cover all pore types of carbonate rocks. Different relationships between porosity, pore throat radius, and permeability have been identified in different patterns, which are utilized to predict more accurate permeability by different pore throat patterns.

A Leap into Automation for Advanced Fracture Characterization

Fractures are the prime conduits of flow for hydrocarbons in reservoir rocks. Identification and characterization of the fracture network yields valuable information for accurate reservoir evaluation. This study aims to portray the benefits and limitations for various existing fracture characterization methods and define strategic workflows for automated fracture characterization targeting both conventional and unconventional reservoirs separately. While traditional seismic provides qualitative information of fractures and faults on a macro scale, acoustics and other petrophysical logs provide a more comprehensive picture on a meso and micro level. High resolution image logs, with shallow depth of investigation are considered the industry standard for analysis of fractures. However, it is imperative to understand the framework of fracture in both near and far field. Various reservoir-specific collaborative workflows have been elucidated for a consistent evaluation of fracture network, results of which are further segregated using class-based machine learning techniques. This study embarks on understanding the critical requirements for fracture characterization in different lithological settings. Conventional reservoirs have good intrinsic porosity and permeability, yet presence of fractures further enhances the flow capacity. In clastic reservoirs, fractures provide an additional permeability assist to an already producible reservoir. In carbonate reservoirs, overall reservoir and production quality exclusively depends on presence of extensive fracture network as it quantitatively controls the fluid flow interactions among otherwise isolated vugs. Devoid of intrinsic porosity and permeability, the presence of open-extensive fractures is even more critical in unconventional reservoirs such as basement, shale-gas/oil and coal-bed methane, since it demarcates the reservoir zone and defines the economic viability for hydrocarbon exploration in reservoirs. Different forward modeling approaches using the best of conventional logs, borehole images, acoustic data (anisotropy analysis, borehole reflection survey and stoneley waveforms) and magnetic resonance logs have been presented to provide reservoir-specific fracture characterization. Linking the resolution and depth of investigation of different available techniques is vital for the determination of openness and extent of the fractures into the formation. The key innovative aspect of this project is the emphasis on an end-to-end suitable quantitative analysis of flow contributing fractures in different conventional and unconventional reservoirs. Successful establishment of this approach capturing critical information will be the stepping-stone for developing machine learning techniques for field level assessment.

An Experimental and Simulation Study of CO2 Sequestration in an Underground Formations; Impact on Geomechanical and Petrophysical Properties

Carbon dioxide (CO2) sequestration is a technique to store CO2 into an underground formation. CO2 can cause a severe reaction with the underground formation and injection tubing inside the well. Successful CO2 storage into underground formations depends on many factors such as efficient sealing, no escaping from the storage, and minimum corrosion to injection tubing/casing. Therefore, proper planning involving thorough study and reaction kinetics of CO2 with the underground formation is indeed necessary for proper planning. The main aim and objective of this study are to investigate the effect of CO2 storage with different cap rocks such as tight carbonate and shale under simulated reservoir conditions. The samples were stored for different times such as 10, 20, and 120 days. The objectives of the study were achieved by carrying out extensive laboratory experiments before and after sequestration. The laboratory experiments included were rock compressive and tensile strength tests, petrophysical tests, and rock mechanical tests. The laboratory results were later used to investigate the reaction kinetics study of CO2 with the underground formation using CMG simulation software. The effect of injection rate, the point of injection, purity of the injection fluid, reservoir heterogeneity, reservoir depth, and minimum miscibility pressure was analyzed. In this simulation model, CO2 is injected for 25 years using CMG-GEM simulation software and then the fate of CO2 post injection is modeled for the next 225 years. The simulation results showed a notable effect on the mechanical strength and petrophysical parameters of the rock after sequestration, also the solubility of CO2 decreases with the increase in salinity and injection pressure. The results also showed that the storage of CO2 increases the petrophysical properties of porosity and permeability of the formation rock when the storage period is more than 20 days because of calcite precipitation and CO2 dissolution. A storage period of fewer than 20 days does not show any significant effect on the porosity and permeability of carbonate reservoir rock. A sensitivity analysis was carried out which showed that the rate of CO2 sequestration is sensitive to the mineral-water reaction kinetic constants. The sensitivity of CO2 sequestration to the rate constants decreases in magnitude respectively for different clay minerals. The new simulation model considers the effect of reaction kinetics and geomechanical parameters. The new model is capable of predicting the compatibility of CO2 sequestration for a particular field for a particular time.