Reservoir Pressure Management Research Articles

Forecast of the future prospects of drilling ultra-deep wells in difficult mining and geological conditions of Western Turkmenistan

The article defines the prospects for drilling wells in difficult and extreme mining and geological conditions of the Western part of Turkmenistan. The assessment of the current state of prospecting and exploration works in Western Turkmenistan is given. The main problems that drillers will face when drilling complex deep horizons of the red-colored stratum are considered, and general principles and recommendations for overcoming these problems are provided. The applied technical and technological innovations that meet international standards have ensured the successful completion of a number of deep and ultra-deep wells in the fields of the West Turkmen Depression, but have not completely solved the existing drilling problems. The article also provides a number of recommendations for solving these problems. This work contributes to the beginning of the development of a new geological and technological discipline - reservoir pressure management during drilling, and its introduction into practice, which will serve as technical re–equipment and organizational restructuring of deep drilling on a scientific basis. Keywords: hydraulic fracturing; collector; sedimentation; gas generation; tectonics; clay solution; reservoir pressure; section; permeability.

A quantitative risk assessment approach for developing contingency plans at a geologic carbon storage site

AbstractGeologic carbon storage (GCS) is an increasingly important technology for reducing carbon dioxide (CO2) emissions to the atmosphere. The leakage risks associated with GCS are an environmental and human health concern, however, and site operators must develop contingency plans that thoroughly consider leakage risks and identify potential mitigation strategies. Here, we use a GCS system model (the National Risk Assessment Partnership's Open‐Source Integrated Assessment Model, NRAP‐Open‐IAM) to evaluate different contingency plans for a hypothetical GCS site. In the scenario considered, an unplugged legacy well is discovered near the site after 5 years of CO2 injection. Our simulations show that the planned operation has a relatively high chance of causing brine leakage through the legacy well and into the two overlying aquifers, the shallower of which has potable water—an unacceptable outcome. To reduce this risk, we consider five remedial response scenarios that manipulate reservoir pressures through brine extraction, injection rate reduction, and early injection stopping. NRAP‐Open‐IAM is used to quantify the degree to which each scenario reduces the probability of brine leakage at the site amidst reservoir uncertainty. Evaluation of the different scenarios suggests that reduction of injection rates effectively reduces leakage risks while maintaining a substantial fraction of the initially intended cumulative CO2 storage. In the event of an emergency, the reservoir pressure management strategies considered here can provide operators more time while they pursue a more permanent solution. The analyses demonstrated here fit into a larger workflow we propose for evaluating the contingency plans of GCS sites. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Particle Swamp Optimized -Physics-Informed Deep Learning for Heterogeneous Oil and Gas Underground Reservoir Pressure Management.

In recent years, Particle Swarm Optimization (PSO) has been integrated with machine learning algorithms, such as deep learning, to create powerful hybrid methods that can tackle complex optimization problems more effectively. In the domain of oil and gas reservoir management, underground pressure management is crucial to maximize the yield and efficiency of the reservoir. However, the heterogeneity of the reservoir, along with uncertainties in its properties, makes pressure management a complex and challenging task. To address this issue, researchers have proposed Physics-Informed Deep Learning (PIDL) techniques that incorporate domain-specific knowledge, such as the governing physical equations, into the deep learning framework. Particle Swarm Optimized-Physics-Informed Deep Learning (PSO-PIDL) is a novel hybrid approach that combines PSO with PIDL to optimize the pressure management of heterogeneous oil and gas underground reservoirs. In this approach, the PSO algorithm is used to find the optimal solution for the PIDL-based model that incorporates the governing physical equations of the reservoir. PSO-PIDL can effectively handle the uncertainties and heterogeneity of the reservoir, while also incorporating the physical constraints of the problem. Overall, PSO-PIDL is a promising approach for optimizing the pressure management of oil and gas reservoirs. It can help reduce the operational costs and improve the efficiency of the reservoir, while also ensuring the sustainable use of natural resources. Keywords: Physics-Informed Deep Learning, Particle Swarm Optimization, Bidirectional Long-Short-Term-Memory, Heterogeneous Reservoir, DuPont Finite Element Heat and Mass Transfer Code

Particle Swamp Optimized -Physics-Informed Deep Learning for Heterogeneous Oil and Gas Underground Reservoir Pressure Management.

In recent years, Particle Swarm Optimization (PSO) has been integrated with machine learning algorithms, such as deep learning, to create powerful hybrid methods that can tackle complex optimization problems more effectively. In the domain of oil and gas reservoir management, underground pressure management is crucial to maximize the yield and efficiency of the reservoir. However, the heterogeneity of the reservoir, along with uncertainties in its properties, makes pressure management a complex and challenging task. To address this issue, researchers have proposed Physics-Informed Deep Learning (PIDL) techniques that incorporate domain-specific knowledge, such as the governing physical equations, into the deep learning framework. Particle Swarm Optimized-Physics-Informed Deep Learning (PSO-PIDL) is a novel hybrid approach that combines PSO with PIDL to optimize the pressure management of heterogeneous oil and gas underground reservoirs. In this approach, the PSO algorithm is used to find the optimal solution for the PIDL-based model that incorporates the governing physical equations of the reservoir. PSO-PIDL can effectively handle the uncertainties and heterogeneity of the reservoir, while also incorporating the physical constraints of the problem. Overall, PSO-PIDL is a promising approach for optimizing the pressure management of oil and gas reservoirs. It can help reduce the operational costs and improve the efficiency of the reservoir, while also ensuring the sustainable use of natural resources. Keywords: Physics-Informed Deep Learning, Particle Swarm Optimization, Bidirectional Long-Short-Term-Memory, Heterogeneous Reservoir, DuPont Finite Element Heat and Mass Transfer Code

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO_2 sequestration and wastewater injection. Managing the pressures by controlling injection/extraction are challenging because of complex heterogeneity in the subsurface. The heterogeneity typically requires high-fidelity physics-based models to make predictions on CO_2 fate. Furthermore, characterizing the heterogeneity accurately is fraught with parametric uncertainty. Accounting for both, heterogeneity and uncertainty, makes this a computationally-intensive problem challenging for current reservoir simulators. To tackle this, we use differentiable programming with a full-physics model and machine learning to determine the fluid extraction rates that prevent over-pressurization at critical reservoir locations. We use DPFEHM framework, which has trustworthy physics based on the standard two-point flux finite volume discretization and is also automatically differentiable like machine learning models. Our physics-informed machine learning framework uses convolutional neural networks to learn an appropriate extraction rate based on the permeability field. We also perform a hyperparameter search to improve the model’s accuracy. Training and testing scenarios are executed to evaluate the feasibility of using physics-informed machine learning to manage reservoir pressures. We constructed and tested a sufficiently accurate simulator that is 400 000 times faster than the underlying physics-based simulator, allowing for near real-time analysis and robust uncertainty quantification.

Extension of CO2 storage life in the Sleipner CCS project by reservoir pressure management

In this study, we performed reservoir simulations to investigate CO2 storage in the saline aquifer in Sleipner by reservoir pressure management. Results show that by producing water at the lowest aquifer structure far away from the CO2-water contact in the vertical direction, an additional 73% (24 Mt) CO2 can be stored compared to the case without water production. This extra CO2 stored can generate a revenue of $800 millions at the prevailing carbon tax of $69 per ton in Norway. There is 5.31 Mtpa of natural CO2 production from 124 gas and oil fields in Norway in 2020. Of these, the Marulk, Dvalin, Skarv, Morvin, Åsgard, Kristin, Tyrihans and Mikkel fields in the Norwegian Sea, and the Kvitebjørn, Valemon, Visund, Gudrun fields in the North Sea produce a total of 4.55 Mtpa CO2 potentially supplying CO2 to Sleipner for project life extension.

Impact potential of hypersaline brines released into the marine environment for CCS reservoir pressure management

The environmental impact potential arising from the possible disposal of hypersaline brines into the ocean as part of reservoir pressure management for Carbon Capture and Storage is assessed using sophisticated high-resolution hydrodynamic models for the first time, investigating several industry guided scenarios. Although the characteristics of some brines in their undiluted form would have a high environmental impact potential, we find that dispersion in a hydrodynamically active region like the North Sea acts to dilute disposed brine rapidly, even in a worst case approach, such that the potential impact footprint (area exposed to environmentally damaging salinity or temperature) is small, measured in 10′s of meters depending on the release scenario and site specific data such as the hypersaline water contaminants along with in-situ conditions such as currents and mixing. The method of brine disposal has a significant influence on dispersal, such that brines released nearer the sea surface disperse more rapidly, compared with release at the seabed. Hence consideration of brine release height is recommended to further limit impact potential.

Sequestering CO2 as CO2 hydrate in an offshore saline aquifer by reservoir pressure management

CO2 has been successfully sequestered in aquifers at shallow water depth as supercritical CO2. However, at a water depth larger than 630 m in tropical regions, there exists a hydrate stability zone (HSZ) extending below the seafloor where CO2 and water can exist as solid CO2 hydrate. It is generally believed that CO2 cannot be stored inside the HSZ as formation of CO2 hydrate will impair CO2 injectivity. In this study, we investigate the feasibility of storing CO2 inside this HSZ by reservoir pressure management vis-à-vis the CO2 hydrate formation pressure through the use of water producers and CO2 injectors.We carry out simulations to investigate CO2 storage in three aquifers in tropical waters each with an area of 94 km2 (9.7 km × 9.7 km), thickness of 50 m, porosity of 30% and permeability of 3,000 md. Three confined aquifers are compared. Aquifer 1 is a shallow water aquifer without a HSZ. It has a water depth of 300 m and buried depth of 830 mbsf. Aquifer 2, straddling (60% inside and 40% outside) the HSZ, has a water depth of 800 m and buried depth of 70 mbsf. Aquifer 3, residing inside the HSZ, has a water depth of 800 m and buried depth of 30 mbsf. The reservoir pressure is managed by four corner wells which function either as CO2 injectors or water producers. We simulate CO2 injection into these aquifers with the help of water production to manage the reservoir pressure to stay below either the reservoir fracture pressure or the hydrate formation pressure.For Aquifer 1, our study shows that by reducing the reservoir pressure to below the fracture pressure through water production, up to 6% PV or 61 Mt of CO2 can be stored. The amount of CO2 stored is limited by the amount of water produced and the breakthrough of CO2 in the water producers. On the other hand, by reducing the reservoir pressure to below the hydrate formation pressure through water production, up to 12% PV or 164 Mt and 21% PV or 13 Mt of CO2 can be stored in Aquifers 2 and 3, respectively.Results show that during CO2 injection, CO2 hydrate formation delays CO2 breakthrough and moderates reservoir pressure due to volume shrinkage thus allowing more CO2 to be stored. Furthermore, over half of the CO2 is stored as immobilized CO2 hydrate which also limits post-injection migration of free CO2 and leakage through the caprock. These results demonstrate the potential of storing CO2 in aquifers having a HSZ with important ramifications for CO2 geological storage.

Measurement of Unloading Pore Volume Compressibility of Frio Sand Under Uniaxial Strain Stress Path and Implications on Reservoir Pressure Management

Measurement of Unloading Pore Volume Compressibility of Frio Sand Under Uniaxial Strain Stress Path and Implications on Reservoir Pressure Management

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

We evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

Active Reservoir Pressure Management with Guidance and Surveillance by Distributed Fiber-optic Strain Sensing

CO2 injection and storage in aquifers can cause pore pressure build up and deformation of the aquifer-caprock system due to extra-fluid accumulation. Active reservoir pressure management, a concept that using brine production before or during CO2 injection to reduce reservoir pressure build up, has been suggested to avoid potential risks posed by geomechanical deformation during large-scale CO2 injection [1], [2]. Sedimentary formations usually develop heterogeneities in fluid properties and mechanical properties. When conducting CO2 injection or brine production, acquiring the in-situ information of pore pressure and fluid distribution and rock deformation would be much helpful for the project operating. In this presentation, we propose to give guidance and surveillance of the CO2 injection and brine production operations in real time using a distributed fiber optic strain sensing (DFOSS) system. We show the field and lab studies and numerical simulation results to demonstrate the feasibility and the advantages when using DFOSS for pressure management in a storage reservoir. Existing difficulties when using DFOSS are also presented.

Developing and validating pressure management and plume control strategies

The U.S. Department of Energy’s (DOE) Office of Fossil Energy (FE) plays a key role in advancing transformative and innovative Carbon Capture Utilization and Storage (CCUS) technologies. In its efforts to ensure safe and secure storage of carbon dioxide (CO2) in a variety of geologic depositional environments, FE is investing in the development of systems for reservoir pressure management in terms of optimizing storage safety and performance. DOE supports a unique set of projects that are exploring brine extraction strategies as an approach to manage reservoir pressure and storage efficiency for CO2 storage sites that may call for such measures. These Brine Extraction Storage Test (BEST) projects have followed a two-phased research approach. Five Phase I projects (completed) carried out modeling and other analyses to support development of pressure management strategies for potential field projects, focusing on five areas/formations representing important potential geologic storage opportunities in the United States. The modeling studies showed how the reservoir characteristics of the various potential storage formations would impact pressure reduction achieved for various injection/extraction scenarios. Life cycle analysis (LCA) studies performed by the projects highlighted the likelihood of encountering very high total dissolved solids (TDS) brines in many saline formation storage projects, as well as the challenges of handling these brines. Two projects have advanced to Phase II (ongoing) to validate brine extraction strategies through injection/extraction of brine and monitoring of differential pressures at active wastewater disposal facilities. Both Phase II projects also host facilities for testing emerging enhanced water recovery (EWR) technologies.

Impact Potential of Hypersaline Brines Released into the Marine Environment as Part of Reservoir Pressure Management

This report describes an assessment of environmental impact potential arising from the possible disposal of hypersaline brines into the ocean as part of reservoir pressure management for Carbon Capture and Storage. We have used sophisticated high-resolution hydrodynamic models to assess a number of guided scenarios. Although the characteristics of some brines in their undiluted form would have a high environmental impact potential, we find that dispersion in a hydrodynamically active region like the North Sea acts to dilute disposed brine rapidly, such that the potential impact footprint (area exposed to environmentally damaging salinity or temperature) is small, generally measured in 10’s of meters depending on scenario and in-situ conditions. Contaminants within the released brines may have more impact potential, depending on concentration. We recommend consideration of brine release height to further limit impact potential.

Stress-dependent fracture permeability measurements and implications for shale gas production

Stress-dependent fracture permeability could significantly affect oil and gas production, underground CO2 storage, and deep waste disposal containment. Yet, measurements to characterize these effects are lacking. To be most relevant to field conditions, measurements of stress-dependent fracture permeability should target pre-existing fracture features, be completed at high-stress conditions, and enable visualization of the fracture geometry to characterize the in-situ aperture profiles. Here, we employ triaxial direct-shear (TDS) tests, integrated with real-time X-ray imaging, to measure the stress-dependent fracture permeability of Marcellus shale and ‘Western Texas’ shale at subsurface conditions. Our results indicate that the studied shale fractures are characterized by large variation of compressibility factor. We also found that surface roughness can reduce fracture permeability more severely than what literature values would suggest. We then implemented our stress-dependent fracture permeability measurements in a formation-linear flow model to investigate the significance for shale gas production. The model uses the MIP-3H well at the Marcellus Shale Energy and Environment Laboratory (MSEEL) as a base case. The model results reveal a narrow stress-dependent permeability range over which fracture closure can be critical for production and that MSEEL appears to be close to this critical condition, which could be important for reservoir pressure management.

On the possibility of operational management of reservoir pressure in a multilayer reservoir exploited by dual completion and injection method based on recording current gas factor of products extracted from each reservoir

The paper discusses the problem of operating complex and expensive telemetering equipment designed to monitor and control a multilayer field operation using the dual completion and injection method. The author offers an alternative to the applied wireless and wired data transmission (as the first type does not have the required range and the second does not have the required reliability) technology. It is a new method for monitoring and controlling reservoir pressure in real time based on recording the current gas factor of the products extracted from each layer using dual completion method and ensuring its relative stability due to the operational management of their reservoir pressure through the dual injection system. At the same time, it is proposed to use commercially available automated group measure unit equipped with corresponding sensors as the means of measuring gas/oil ratio. Testing the method of reservoir pressure management proposed by the author for the two-layer reservoir of the Tedinskoye field of Lukoil-Severneftegaz confirmed its effectiveness, which served as the basis for the development of an appropriate methodological guide and filing of a patent.

Pressure management via brine extraction in geological CO2 storage: Adaptive optimization strategies under poorly characterized reservoir conditions

Industrial-scale injection of CO2 into the subsurface increases the fluid pressure in the reservoir, which if not properly controlled can potentially lead to geomechanical damage (i.e., fracturing of the caprock or reactivation of faults) and subsequent CO2 leakage. Brine extraction is one approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. The management of the extracted brine can be expensive (i.e., due to transportation, treatment, disposal, or re-injection), with added cost to the carbon capture and sequestration (CCS); thus, minimizing the volume of extraction brine is of great importance to ensure that the economics of CCS are favorable. The main objective of this study is to demonstrate the use of adaptive optimization methods in the planning of brine extraction and to investigate how the quality of initial site characterization data and the use of newly acquired monitoring data (e.g. pressure at observation wells) impact the optimization performance. We apply an adaptive management approach that integrates monitoring, calibration, and optimization of brine extraction rates to achieve pre-defined pressure constraints. Our results show that reservoir pressure management can be extremely benefited by early and high frequency pressure monitoring during early injection times, especially for poor initial reservoir characterization. Low frequencies of model calibration and optimization with monitoring data may lead to optimization problems because either pressure buildup constraints are violated or excessively high extraction rates are proposed. The adaptive pressure management approach may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the volumes of extracted brine while controlling pressure buildup.

A Field Demonstration of an Active Reservoir Pressure Management through Fluid Injection and Displaced Fluid Extraction at the Rock Springs Uplift a Priority Geologic CO2 Storage Site for Wyoming

The University of Wyoming is partnered with Los Alamos National Laboratory, Lawrence Livermore National Laboratory, Battelle, and Water system Specialists Inc. to carry out a DOE funded brine extraction storage test (BEST) project at the Rock Springs Uplift (RSU), southwest Wyoming. The BEST projects are envisioned using a two-phased approach. The initial phase is 1) to predict and monitor the differential pressure and injected fluid movement, and manage changes in formation pressure, and 2) to develop a test-bed for deploying treatment technologies for extracted brines.The RSU shows promise as a CO2 storage location because of its favorable geologic conditions and structure. In addition, the project is located at a carbon storage site in southwest Wyoming that has been extensively characterized on the basis of data obtained from previous U.S. DOE-funded studies that have included detailed site descriptions and CO2 storage capacity and permanence estimates. The primary objective of the project includes:•Refining 3-D reservoir structure and property models of the site that include the known structural complexity and heterogeneity of the site's subsurface conditions;•Evaluate geophysical and chemical monitoring technologies and techniques to detect and measure pressure response to injected fluid as well as track fluid migration pathways;•Analyze the feasibility of extracting formation brine water to mitigate the pressure increase from injection, as well as to modify the pressure front, resulting in the ability to manipulate the direction of the migrating pressure/CO2 plume, and reduce the size of the Area of Review;•Develop advanced fluid flow simulation schemes to predict reservoir pressure responses and migration pathways of the injected fluid;•Implement rock mechanical property and stress calculations, combined with simulations, to help assess geomechanical impacts to the reservoir and confining layers in response to high volume CO2 injections;•Conduct a produced brine life-cycle analysis, and develop a displaced brine water treatment, and management program; and•Propose an active reservoir management strategy that could be implemented during a field testing.The proposed field test project includes developing a field site fully capable of fluid injection, production, monitoring, and water treatment. This effort would provide for in-situ testing of plume migration and pressure management strategies, and investigate the technical feasibility of treating co-produced waters. Furthermore, the result of this effort is a better understanding of the potential effects of pressure and active brine management on the behavior of stored CO2 in the Rocky Mountain region as well as the similar saline aquifers around world, such as the huge saline aquifer in the Ordos Basin, China.

Multifluid geo-energy systems: Using geologic CO2storage for geothermal energy production and grid-scale energy storage in sedimentary basins

We present an approach that uses the huge fluid and thermal storage capac­ity of the subsurface, together with geologic carbon dioxide (CO 2 ) ­storage, to harvest, store, and dispatch energy from subsurface (geothermal) and surface (solar, nuclear, fossil) thermal resources, as well as excess energy on electric grids. Captured CO 2 is injected into saline aquifers to store pressure, generate artesian flow of brine, and provide a supplemental working fluid for efficient heat extraction and power conversion. Concentric rings of injection and production wells create a hydraulic mound to store pressure, CO 2 , and thermal energy. This energy storage can take excess power from the grid and excess and/or waste thermal energy and dispatch that energy when it is demanded, and thus enable higher penetration of variable renewable energy technologies (e.g., wind and solar). CO 2 stored in the subsurface functions as a cushion gas to provide enormous pressure storage capacity and displace large quantities of brine, some of which can be treated for a variety of beneficial uses. Geo­thermal power and energy-storage applications may generate enough revenues to compensate for CO 2 capture costs. While our approach can use nitrogen (N 2 ), in addition to CO 2 , as a supplemental fluid, and store thermal energy, this study focuses on using CO 2 for geothermal energy production and grid-scale energy storage. We conduct a techno-economic assess­ment to determine the levelized cost of electricity using this approach to generate geothermal power. We present a reservoir pressure management strategy that diverts a small portion of the produced brine for beneficial consumptive use to reduce the pumping cost of fluid recirculation, while reducing the risk of seismicity, caprock fracture, and CO 2 leakage.

Coupled Hydro-Mechanical Simulations of CO2Storage Supported by Pressure Management Demonstrate Synergy Benefits from Simultaneous Formation Fluid Extraction

We assessed the synergetic benefits of simultaneous formation fluid extraction during CO 2 injection for reservoir pressure management by coupled hydro-mechanical simulations at the prospective Vedsted storage site located in northern Denmark. Effectiveness of reservoir pressure management was investigated by simulation of CO 2 storage without any fluid extraction as well as with 66% and 100% equivalent volume formation fluid extraction from four wells positioned for geothermal heat recovery. Simulation results demonstrate that a total pressure reduction of up to about 1.1 MPa can be achieved at the injection well. Furthermore, the areal pressure perturbation in the storage reservoir can be significantly decreased compared to the simulation scenario without any formation fluid extraction. Following a stress regime analysis, two stress regimes were considered in the coupled hydro-mechanical simulations indicating that the maximum ground surface uplift is about 0.24 m in the absence of any reservoir pressure management. However, a ground uplift mitigation of up to 37.3% (from 0.24 m to 0.15 m) can be achieved at the injection well by 100% equivalent volume formation fluid extraction. Well-based adaptation of fluid extraction rates can support achieving zero displacements at the proposed formation fluid extraction wells located close to urban infrastructure. Since shear and tensile failure do not occur under both stress regimes for all investigated scenarios, it is concluded that a safe operation of CO 2 injection with simultaneous formation fluid extraction for geothermal heat recovery can be implemented at the Vedsted site.

Some data on two-tier impellers of pumps for reservoir pressure maintenance systems

In this article, data are reported on creation of a two-tier impeller for a centrifugal pump in the reservoir pressure management (RPM) system. The design was based on numerical experiment performed with the aid of ANSYS CFX 11 software. The new design of the impeller with addition of a second row of blades made it possible to heighten the (pressure) head to the required level while retaining the efficiency of the basic design. A comparison of full-scale test data for a batch of pumps with a fixed set of modernization and forecast characteristics showed fairly good agreement. The two-tier impeller test data help consider such a method of elevating impeller head promising. The work on the determination of the influence of geometry of the second tier (row) of blades on variation of head and efficiency should be continued.