Suresh Kumar Govindarajan’s Post

AI/ML in Reservoir Engineering (CBM Reservoir)   1.    How exactly AI/ML would be able to distinguish the following two scenarios, associated with stress-dependent permeability, while training the data? (a)             Permeability reduction from enhancement in effective stresses associated with fracture aperture compression during drawdown of a reservoir by primary production (Fractured Reservoir) (b)            Permeability enhancement resulting from enhancement in cleat thickness associated with the desorption of methane following drawdown (CBM Reservoir)    2.    Using AI/ML, would it remain feasible to forecast (a)             the permeability rebound associated with the field conditions as a function of Langmuir parameters, Young’s modulus & porosity @ virgin reservoir pressure (b)            matrix shrinkage ratio between CO2 & CH4 (c)             ability/inability of cleats to close on asperites or mineralization (d)            degree of dilatancy associated with the enhanced projection of permeability (changes in stress induced by matrix shrinkage associated with drawdown profile) (e)             pore volume compressibility as a function of matrix shrinkage & changes in drawdown and effective stress (f)              porosity changes as a function of changes in permeability for various Young’s modulus   3.    Whether the Langmuir parameters associated with coal matrix shrinkage observed at the laboratory-scale be used for training data in order to forecast the field scenario? Suresh Kumar Govindarajan https://lnkd.in/d6rtS6Ue https://lnkd.in/d_miY7ZU

Carbonate Reservoir Characterization: Part 01 1.     It is known that carbonate sediments have a wide range of particle size and sorting resulting from complex organic processes which gets redistributed with time leading to porosity values ranging between 40 and 75%, while, permeability values ranging between 200 and 30,000 md. If so, how should the fundamental approach of a carbonate reservoir characterization should vary for (a) mud-dominated fabrics (with 70% porosity & 200 md permeability); (b) grain-dominated pack-stones (with 50% porosity & 2000 md permeability); and (c) grain-stones (with 40% porosity and 30,000 md permeability)? 2.     Do we also consider the primary environmental factors (affected by physical, chemical & biological conditions of the depositional settings); and the details of the secondary diagenetic processes, while, characterizing a carbonate reservoir?  3.     How exactly do we capture the details on the variations of the facies changes (which modify rock properties over tens of meter scale) as against the changes associated with diagenetic processes (which modify rock properties @ smaller scales), associated with a carbonate reservoir? 4.     Feasible to couple the factors controlling the quality of a carbonate reservoir with that of the drainage mechanism of a carbonate reservoir, which includes (a) geological-age (depo-time); (b) type of carbonate platform (depo-system); (c) facies belts (depo-zone); three-dimensional geometrical classification (depo-shape); (d) building blocks of the depo-shape (depo-element); and (e) carbonate lithofacies? 5.     To what extent, the details (lithology, type and frequency of allochems, microscopic sedimentary features such as bioturbation, presence of opaque materials, laminations, mud cracks, brecciation and fenestral fabric of the samples, type and frequency of various pore types, fractures, cements and compaction features) from a thin section analysis could be converted into its equivalent rock and fluid properties in a carbonate reservoir? 6.     Whether computed tomography scanning (CT scan) would be able to identify the presence of fractures @ core-scale? Feasible to capture the details on fracture length, fracture aperture thickness, fracture width and fracture spacing? 7.     To what extent, the direct data deduced from cores will precisely reflect geological, petro-physical, geo-mechanical and geo-chemical properties of a carbonate reservoir? 8.     Since, indirect measurements have two different spatial scales: (a) wire-line logs @ relatively smaller scales [0.15 m]; and (b) seismic sections @ relatively larger scales; whether, how exactly, these two measurements will be representing a carbonate reservoir, on a common spatial scale? Suresh Kumar Govindarajan https://lnkd.in/d6rtS6Ue https://lnkd.in/d_miY7ZU

Characterization of Primary and Secondary Recovery Processes in an Oil Reservoir: Theoretical Assumptions and Experimental Limitations Part 01 1.     If capillary and gravity forces dictate the vertical equilibrium of pore fluid distribution in an oil reservoir, before drilling, then, how come these two fundamental forces can be assumed to be ignored (during oil production), while developing mathematical models in order to characterize fluid flow through an oil reservoir by considering only viscous effects (in the absence of inertial effects)? Won’t we have both horizontal as well as vertical components of capillary forces upon oil production? 2.     If only viscous effects are considered to be responsible for fluid flow towards production well in an oil reservoir (following production operations), using original Darcy’s law, then, only pressure-gradient and mobility (k/μ) plays a role – towards characterizing fluid flow - in the absence of any scope for the capillary pressure (saturation gradient) and gravity effects (density gradient). Can such simplified Darcy’s law be used for characterizing two-phase fluid flow in an oil reservoir by just introducing the concept of ‘relative permeability’; and by having an individual flow equation for oil and water phases? 3.     What is the physical significance of the endpoints of oil and water relative permeability curves observed at the laboratory-scale? Whether the immobile water saturation of the core plug at the start of the water-oil relative permeability experiments @ laboratory-scale – would remain to be exactly equal to the connate water saturation of an oil reservoir, located above the oil-water transition zone @ field-scale? Feasible to retain original reservoir wettability conditions @ laboratory-scale? Won’t it require a significantly longer time in order to capture the true value of residual oil saturation @ laboratory-scale? Apart from the value of initial water saturation, to what extent, the laboratory-scale values of (a) residual oil saturation; (b) oil relative permeability @ initial water saturation; and (c) water relative permeability @ residual oil saturation – remain meaningful at larger field-scale? Feasible to conduct the above experiments using core plugs that exactly reflects the values of ‘field-scale’ ‘reservoir porosity’ and ‘reservoir permeability’? Suresh Kumar Govindarajan https://lnkd.in/d6rtS6Ue https://lnkd.in/d_miY7ZU

The following is a paper on Tesseral AI's Duplex Wave Migration (DWM). DWM studies have been done and it has been shown that Tesseral AI can show the fluids that are in the fractures. The fractures can be seen as permeability pathways and can help with reservoir simulations. With CCS understanding the fracture network will become important as steep dipping faults may be pathways for the CO2 to escape. If fluids can be seen then DWM can be used in 4D projects to see how the CO2 is moving through the rock. Think of DWM and it is being used in carbonate reservoirs for the reservoir simulation and to determine placement of wells. This is where geoscience and reservoir engineering intersect.

𝗥𝗲𝘀𝗲𝗿𝘃𝗼𝗶𝗿 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻👨💻 in a nutshell😊 Do you know! Reservoir modeling and simulation is the most powerful tool to interpret, visualize, and analyze oil and gas reservoirs. It's an area of reservoir engineering that, combines 𝙥𝙝𝙮𝙨𝙞𝙘𝙨, 𝙢𝙖𝙩𝙝𝙚𝙢𝙖𝙩𝙞𝙘𝙨, and 𝙘𝙤𝙢𝙥𝙪𝙩𝙚𝙧 𝙥𝙧𝙤𝙜𝙧𝙖𝙢𝙢𝙞𝙣𝙜 to a reservoir model allows the analysis and the prediction of the fluid behavior in the reservoir over time. It can be simply considered as the process of mimicking the behavior of fluid flow in a petroleum reservoir system( including reservoir rock and fluids, aquifer, surface, and subsurface facilities) through the use of either physical or mathematical models. Reservoir simulation consists of: ➣a geological model in the form of a volumetric grid with cell/face properties that describe the given porous rock formation. ➣a flow model that describes how fluids flow in a porous medium, typically given as a set of partial differential equations expressing the conservation of mass or volumes together with appropriate closure relations. ➣a well model that describes the flow in and out of the reservoir, including a model for flow within the well bore and any coupling to flow control devices or surface facilities Reservoir simulation is used for two main purposes: ➣to optimize development plans for new fields ➣to assist with operational and investment decisions. The main elements of a simulation study include ➣matching field history ➣making predictions (a forecast based on the existing operating strategy) ➣evaluating alternative operating scenarios. To become an expert in reservoir modelling, join our upcoming live training. Register now: https://lnkd.in/em_VNVtg 📅 Dates: 𝟭𝟲𝘁𝗵 𝗗𝗲𝗰𝗲𝗺𝗯𝗲𝗿 𝟮𝟬𝟮𝟯 Onwards - 9:30 Pm Indian Time ⌚ Duration: 𝟮 𝗪𝗲𝗲𝗸𝘀 - 𝟯 𝗛𝗼𝘂𝗿𝘀 / 𝗗𝗮𝘆 🖥️ Format: 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 #oilandgas #reservoirsimulationcourse

Based on the analysis of factors influencing #fluid infiltration in #porous media, this book systematically summarizes the characteristics and expressions of low-velocity #nonlinear flow and high-velocity nonlinear flow infiltration in porous media and provides a set of evaluation methods. Using the exponential formula, the starting pressure gradient formula, and the binomial equation of motion, the authors present a detailed comparison and analysis of the production, pressure, and dimensionless background pressure of the nonlinear flow and Darcy linear flow for steady and unsteady flow. In addition, based on the equation of motion of the starting pressure gradient, a mathematical model of the one-, two-, and three-medium nonlinear seepage flow is established, and approximate analytical solutions are given while the graph of the corresponding well test curve is drawn. Finally, based on the mathematical model of the well test established from the exponential equation of the high-velocity nonlinear flow motion, the atypical well test curve and the relational surface of the time- and space-varying infiltration index are obtained. The authors also discuss the relationship between reservoir and fluid properties and the nonlinear flow test curve. This book is intended to serve as a reference for technical personnel, researchers, teachers, and students involved in oil and gas development. Its research contents provide a theoretical basis for the identification of water flow dominant channels in the long-term water injection development of high-water-cut oilfields, profile control and water shut-off, productivity evaluation of carbonate reservoirs and formation parameters. More information about the book: https://bit.ly/4a5xUeV #engineering

Characterization of Primary and Secondary Recovery Processes in an Oil Reservoir: Theoretical Assumptions and Experimental Limitations   Part 16 1.     If a reservoir remains to be highly heterogeneous, characterized by highly stratified carbonate, having significant variations in porosity and permeability, both areally and vertically, then, to what extent, the application of water-flooding with various pattern layouts and well-spacing would remain to be successful? 2.     Would it remain feasible to have the following details at the earliest in a field-scale scenario, following primary production and during the commencement of secondary oil recovery? (a) major producing zone, where oil keeps flowing with ease; (b) a producing oil-water contact, below which, only brine was produced during primary and secondary recovery operations; (c) a residual oil zone, where oil saturation remains to be immobile; and (d) a free water level, below which, we have 100% water saturation. Based on these details, would it remain feasible: (a) To assess the remaining hydrocarbon reserves under current operations? (b) To delineate the possible changes in order to enhance secondary recovery under current operations? (c) To determine the feasibility of infill drilling – by carrying out surveillance programs; areal flood balancing; injection, production, vertical conformance & pattern performance monitoring; and optimization? Further, would it remain practically feasible in order to maintain a relatively higher water-oil ratio in order to achieve higher oil recovery by producing, separating, reinjecting and recycling large volumes of water on a daily basis @ field-scale? 3.     Feasible to investigate the fundamental physics associated with a water-flooding mechanism of a large, high-porosity, fractured chalk oil reservoirs containing a low-viscosity, high formation volume factor light oil, where both imbibition and viscous displacement dominates @ laboratory-scale using experimental investigations (that impacts the reservoir behavior and its associated oil recovery efficiency)? 4.     Does water injection induce shear in a carbonate reservoir? Whether the coupled effect of shear failure and water weakening of the rock matrix result in additional deformation of the carbonates, even under conditions of constant or decreasing stress levels? Suresh Kumar Govindarajan https://lnkd.in/d6rtS6Ue https://lnkd.in/d_miY7ZU

Besides the above mentioned, MWD and LWD logs also plays a very vitol role, it utilize specialized drill collars and data telemetry systems that allow most wireline measurements to be made, as the well is being drilled. Because MWD/LWD systems commonly use mud-pulse telemetry, they are real-time measurements, compared to wireline measurements, which are made only at casing points. They were developed for use in high-risk wells and for high-angle deviated or horizontal wells, which were difficult to log with wireline methods. The LWD/MWD measurements are used during geosteering operations in deviated and horizontal wells.

Carbonate Reservoir Characterization: Part 03 1.     In a typical carbonate reservoir, does the saturation of a non-wetting phase depend on any other function than (a) the interfacial tension between non-wetting and wetting phases; (b) the adhesive forces between the fluids and the minerals that make up the pore walls; (c) the pressure differential between the non-wetting and wetting phases; and (d) pore-throat size? 2.     In general, the pressure differential between non-wetting and wetting phases (capillary pressure) is produced by the difference in density between non-wetting and wetting phases resulting from buoyancy effect (produces pressures in hydrocarbon column). If so, in a carbonate reservoir, whether the pressure in the wetting phase will remain to be equal to the difference between (a) the reservoir pressure @ zero capillary pressure; and (b) the height above the zero capillary pressure times water density? 3.     Whether the pressure gradient in a carbonate reservoir (measured from repeat formation tester or a wireline formation tester) be used to estimate the distance above the zero capillary pressure level? 4.     In a fractured carbonate reservoir, whether, the pressure difference between the oil phase and water phase would remain to be equal to the difference between the specific gravity of the two fluids multiplied by the height of the oil column @ any given height in an oil column? 5.     Would it remain feasible to deduce the base of a carbonate reservoir either by using drainage curve or by using imbibition curve? 6.     Which of the following geological conditions remain to be very sensitive in generating fractures along with fracture spacing, fracture width and fracture dip: (a) depth of burial; (b) thickness of beds; (c) changes in lithology; (d) local stress field including the amount of differential stress considering mechanical discontinuities; (e) physical/chemical/mechanical properties of rocks and fluids in the pores; (f) rate of over-burden loading/unloading; and (g) gravitational compaction? 7.     Permeability being dependent upon both volume of the rock sample and orientation, how do we take into account the influence of fractures and stylolites – present in the core samples - during permeability measurement? How exactly a carbonate reservoir formation needs to be sampled before using it for experimental investigations @ laboratory-scale? 8.     Feasible to have a direct relation between porosity and permeability in the absence of having pore-size distribution in a carbonate reservoir? 9.     How exactly to treat a carbonate reservoir system having a distinct fracture permeability and a matrix permeability? Suresh Kumar Govindarajan https://lnkd.in/d6rtS6Ue https://lnkd.in/d_miY7ZU

Thermodynamic Modelling of Rare Earth Solvent Extraction with Brett Schug from SysCAD. Rare Earth Elements (REEs) are becoming increasingly important due to their critical role in energy transition. In recent times, there has been significant activity and investment in production from mining and recycling. A key area of difficulty for metallurgical production of REEs is their separation, largely due to their similar electron structures which makes them chemically similar. In this work, a thermodynamic model of solvent extraction (SX) is presented based solely upon experimental data in the open literature using the PHREEQC (USGS, 2021) interface with SysCAD. In previous work, Heppner (2021) calculated reaction equilibrium constants for the extraction of Nd and Pr based upon fitting to experimental data of Lyon et al. (2017). Here, that model is extended using separation factors published by Zhang et al. (2020) and references therein to estimate the equilibrium constants for all 15 REEs. Pitzer parameters and their temperature dependence are calculated for each cation-anion interaction in the REE chloride system from correlations published by Simoes et al. (2016, 2017). It is noteworthy that aqueous/organic exchange reactions are written in terms of free acid, not hydrochloric acid, and thus, are suitable for use in any acidic medium (e.g. chloride, sulphate, nitrate). A test of the model was performed where a solution containing REE chlorides was fed to an extraction, scrubbing, and stripping circuit with conditions typical for initial separation of light, medium, and heavy REE elements. Results of the test model show typical trends in the SX separation of REEs, confirming the validity of the approach. This fundamental approach enables a wider range of applicability for the model compared to the use of plant isotherms. This work focuses on the modelling methodology of the REE SX process, rather than the modelling of a specific processing plant. For this reason, the presented model requires validation against relevant plant data prior to use for plant design or optimization. https://lnkd.in/eRupYvVN #ALTA2024