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Summary The microscopic displacement efficiency of supercritical carbon dioxide (CO2)-based enhanced oil recovery (EOR) depends critically on the phase behavior of CO2 and residual oil. Traditionally, we assume that the main drive mechanisms of supercritical CO2 EOR are attributed to oil swelling and reduced oil viscosity, and research focuses on how the supercritical CO2 interacts with remaining oil under the reservoir conditions. However, our recent study finds that once the CO2 is introduced into the reservoir, CO2 partitions into the aqueous and oil phases, reducing the interfacial tension (IFT) between the oil and water. This is particularly important when CO2 is generated through a series of chemical reactions for in-situ CO2 EOR. In this paper, we used molecular dynamics (MD) simulations to study the interfacial properties between water and oil with different mole fractions of CO2 in pressures below the minimum miscibility pressure. Simulation results show that with the increase in CO2 mole fraction, rather than evenly distributed in phases, CO2 molecules are prone to concentrate in the water/oil interface region, which decreases IFT between the aqueous phase and oil. Furthermore, the effect of CO2 orientation on the water/oil IFT reduction was observed. The change of CO2 concentration affects CO2 orientation near the interface, which in return dominates the IFT change.

Produced water is commonly co-produced with oil and gas production and requires safe disposal in subsurface reservoirs. Knowing the amount of produced water that can be safely injected into the reservoir is important for disposal operations. While the methods of reservoir hydrocarbon storage are abundant in literature, the granularity of handling water injection capacity is rare, probably due to the misconception that production is similar to injection into a formation. The knowledge of hydrocarbon reservoir petrophysics shines some light on the problem. However, it is far from sufficient to make an economically viable decision as injecting water into the reservoir dramatically differs from producing it. Many practitioners take for granted that knowing the pore volume of the target formation would be sufficient to determine the storage volume. The actual water injection capacity is the product of the pore volume of the formation, total compressibility of the system, and maximum allowable pressure difference. Since the stress-strain relationship of a porous medium depends on the frequency and magnitude of the loading and unloading process, the total compressibility would be different. The maximum allowable injection pressure and reservoir pressure are functions of in-situ stresses, injection temperature and pressure, and reservoir geomechanical parameters, all of which have significant uncertainty. In practical design, we must consider all parameters and their respective uncertainties. This paper presents a procedure for determining the injection capacity through an in-depth discussion of involved parameters and their associated uncertainties from estimation and measurements. This paper will also demonstrate our practice using a field example as our case study to show our suggested approach.

Laboratory experiments have demonstrated that injecting urea solution as a CO2-generating agent into an oil reservoir may significantly enhance oil recovery. When the reservoir temperature is above 50°C, urea is hydrolyzed to carbon dioxide and ammonia. This technology overcomes many supercritical CO2 problems and can be very attractive for thousands of stripper wells that produce oil on marginal economic feasibility. However, previous efforts mainly focus on laboratory tests and mechanisms study. The actual field performance of this technology is likely dependent on reservoir heterogeneity, and its economic viability is expected to be closely related to its optimization. This highly relies on numerical modeling and simulation capability. The synergic mechanisms in in-situ CO2 EOR (ICE) using urea are complex. Firstly, the decomposition of urea injected leads to CO2 and ammonia under proper reservoir conditions. The generated CO2 in brine partitions preferably into the oil phase and decreases oil viscosity while swelling the oil effectively. The co-generated product, ammonia, can potentially reduce the interfacial tension (IFT) between the oil/water phase, which moves the relative permeability (or saturation) curves and position to offer additional oil production. In the first attempt, the dominant parameters, including urea reaction kinetics, the stoichiometry of the decomposition process, the oil swelling effect, and the impact of IFT reduction on the relative permeabilities, were considered and incorporated into the numerical modeling effort. We used the chosen numerical simulations to determine the contribution of the individual mechanism by history matching the results of laboratory tests collected previously. The one-D mechanistic numerical model was then upscaled to a synthetic homogeneous 3D model by simulating a quarter of the 5-spot sector model to evaluate the feasibility and engineering design of ICE for future field scale pilot tests and potential prize of ICE EOR. After comparing the base case with urea injection, a sensitivity analysis was performed. As part of the aims, the simulation results differentiate and reveal the incremental contributions of the synergetic behaviors among several mechanisms: oil viscosity reduction, oil swelling, and IFT reduction. Data also showed that the IFT reduction plays a rather minor role in this effort, and its contribution is basically indistinguishable. The predominant recovery mechanisms are mainly controlled by oil swelling and viscosity reduction; temperature plays a key role in influencing the extent of reaction kinetics of urea. In the 1D simulation, the temperature significantly impacted the production performance as the core cooled down quickly. In a 3D or field-scale scenario, the waterflooding does not change the in-depth reservoir temperature as the temperature gradient moves at a much slower rate (about two times slower) than the injected urea solution slug. However, the duration of water flooding should be considered for field project design as it may alter the temperature profile in the reservoir.

As more and more water is being co-produced with hydrocarbon, saltwater management has become an important enterprise. Out of many available tools in water management, saltwater disposal through Type II wells is critical to handling large quantities of produced brine. Since the produced water usually contains impurities such as solids, oil and grease, and bacteria, the well's injectivity deteriorates over time as the skin factor develops. Injecting over the formation parting pressure (FPP) gradient may lead to a matrix bypass event and other geohazards; accurately determining the FPP of the target formation is needed to maintain safe injection operations. However, using the step rate test (SRT) doesn't warrant an accurate result. As the target formations can have multilayers with distinct properties, we often find that SRT is often misused. SRT is often recommended based on oil field operational experience because it is easy to execute and interpret. One fundamental assumption for SRT is that the target formation is a single layer with relative isotropic properties; however, this isn't always true for saltwater disposal wells (SWDs), which usually penetrate through multilayers with very heterogeneous properties. To illustrate our concept, we present a case study using SRT results from an active SWD well located in the Anadarko Basin. We recommend a geomechanical model to determine the operating surface pressure in this paper. The geomechanical model considers the original stresses, variation of geomechanical parameters, injection pressure, and temperature. To consider the uncertainties of these parameters, we demonstrate how to use Monte Carlo simulation to determine the maximum operating surface pressure. We recommend several analyses for the collected data to determine the well's injectivity variation. The Monte Carlo simulation result yields a possible fracturing gradient and presents the probability of each fracturing gradient. Probability is crucial in decision-making as different operators/fields may have different risks, tolerance, and uncertainties. The recommended practice is an integration of data sets and analysis that yield the maximum injection pressure to maintain the well and formation integrity with different risk tolerance levels.

When operators develop shale gas reservoirs in the southern Sichuan basin in China, they encountered numerous occurrences of casing deformations (CD) and even failures. The high frequency and severity of CD have led to significant financial loss. Since then, a considerable amount of research has been conducted with some field trials. Some research findings have been implemented in fields. The purpose of this paper is to present what we know and the trial results. We observed that casing deformation/failure were mainly in shearing failure and collapse modes. In the early stage of the development, most of the failure was due to shearing deformation caused by pre-existing geological features such as faults and weak interfaces. With the depletion of the reservoir and pressure decrease, casing collapses during the hydraulic fracture with extended length have become more and more popular in the later development stage. Laboratory tests on casing material and cementing material have shad lights on possible solutions. Increasing the casing wall thickness and cement thickness seems a viable solution for casing collapse, but the application of these recommendations yielded little effectiveness in mitigating casing deformation. Current operators redesigned a cementing material with high-strength beads which would collapse when stresses are above the designed threshold, which would "absorb" the formation displacement and reduce the severity of casing deformation caused by the aforementioned mechanisms. This paper summarizes the main research results from implementing numerical modeling and simulation. Based on that, we designed a special cementing with hollow high-strength particles in the cement slurry. In the later stage of fracturing, when the stress is above a threshold, the particles would burst and allow the casing to nudge slightly so that the deformation severity would be much less and more graduate. We implemented the new technology on 14 wells, and so far eight wells have been successfully completed without losses of horizontal segments. This new technology certainly brings hope for future study and provides field cases for future simulation work and laboratory studies for improvement.

Generating production-type curves for new horizontal wells in unconventional reservoirs is an evolving process that requires continuous calibration to maintain the most accurate forecast over time. History matching production alone is no longer sufficient to maintain such models. Obstacles to creating production type curves are attributed to the complexities in heterogeneous reservoir properties, improved drilling and completion techniques, and evolving production and operation procedures. This paper will highlight improvements to a proposed machine-learning algorithm to generate production type curves for new wells in oil and gas unconventional reservoirs. The algorithm utilizes dimensionless groups created from the raw data in different categories and scales, thus reducing the dimension of the problem, decreasing the processing time, and improving the efficiency of the machine-learning model. The dimensionless groups are developed using inspectional and dimensional analysis depending on the data available for feature inputs. Many of the dimensionless groups have physical meanings and can be upscaled. We advanced the ability of the previously developed algorithm utilizing production, completion, and petrophysical data from both oil and gas reservoirs to generate new type curves by using the "engineering" code that was laid out in our previous case study. The algorithm incorporates physics into the machine learning (ML) process supporting the outputs with math and science. When using multiple reservoirs from different formations in the data, the algorithm utilizes logic in the code to determine between oil and gas wells. The quality of the results is impacted when using data from reservoirs with phase envelopes that are not similar, for example, a heavy oil and a dry gas reservoir. The algorithm is updated to include logic that can determine the major phase to predict oil and gas production more accurately. The quantity of oil and gas production is more accurately predicted using cumulative production rates rather than over time. The machine learning model maintains an R2 >= 0.8 when cross-validating both cumulative oil and gas production. The algorithm consistently predicts cumulative production over time on test data with R2 >=0.8. The predicted rates for new type curves are compared to conventional production type curves, thus validating the quality and goodness of fit for production rates, decline profile, and ultimate recovery. The results demonstrate how late-time production can be either extrapolated using the machine learning algorithm or combining traditional methods by utilizing hyperbolic and exponential declines where training data is unavailable for the machine learning model to perform late-time forecasting. The algorithm of the ML model is proving to be a supplementary tool when generating new production type curves. The speed and efficiency provide support to the DCA generated type curves. It is versatile in its ability to combine data from multiple formations and discern between the major phase, thus providing production type curves we have confidence. The scalability of the dimensionless input parameters can account for changes in completions and reservoir properties within minutes of updating the database hence providing insight in near real-time for engineers.

Forecasting production from unconventional reservoirs is a slippery slope that could lead to unrealistic results even though a model has been history matched with production history and vetted by experienced engineers. The reasons for failing conventional decline curves lie in convoluting and heterogeneous reservoir properties, advancing drilling and completion techniques, and dynamic production and operations management. However, the initial rates, declining rate, and ultimate recovery of a well can be viewed as relatively static and predetermined properties of a declining profile. This paper will propose a machine learning-based framework to determine these properties for unconventional reservoir development. In the proposed algorithm, instead of directly data mining on the raw data from different categories and scales, we propose to convert these data into dimensionless variable groups to reduce the dimension of the problem. The dimensionless variables are developed using inspection analysis; most have physical meanings and are easy to upscale. In the case study, we used the production, completion, and petrophysical data to generate new type curves and developed a step-by-step process to explain the aspect of "engineering" code that incorporates physics into the machine learning (ML) process. Dimensionless variables are used in the machine learning process giving physical meaning and reducing the number of predictors, thus improving the speed and efficiency of the code. The results show that the quantity of cumulative oil production over time can be determined using machine learning models with R2 >= 0.90 for individual wells and R2>=0.80 for cross-validated cumulative production forecasts. We can use these determined values to assess the quality of initial rates, declining rates, and ultimate recovery to derive new type curves that incorporate physics and engineering practices. The work emphasizes the importance of accounting for completion parameters, fluid properties and rock quality, thus improving the confidence in results obtained through traditional engineering methods. The machine learning model results provide credibility and support to rates and recoveries for DCA forecasted wells. When modeling hundreds if not thousands of wells, this work shows the importance of utilizing machine learning to harness the power of the data that has been collected on them. The machine-learning-based declining profile is a promising technique and has some advantages over the classical methods based on averaging historical data. First, the determining parameters are highly scalable for newly drilled wells as the main input parameters are dimensionless variables derived from reservoir properties and well completions. Secondly, this algorithm explores not only the production data but also reservoir properties and completion data to capitalize on the advancing techniques.

In this study, molecular dynamics simulations have been performed to study the interfacial properties between water and oil with different mole fractions of CO2 under 8 MPa and 345 K. Simulation results show that with the increase of CO2 mole fraction, more CO2 got adsorbed in the water-oil interface region. Such CO2 increase weakened water and oil interactions at the interface, resulting in a decrease of the interfacial tension (IFT). Moreover, the water-oil IFT decreased significantly from 0 to 0.40 CO2 mole fractions. But the change was small for higher CO2 mole fractions of 0.40 to 0.80. From those calculations, we conclude that in the CO2-EOR, the volume of injected CO2 needs to be at least more than 0.4 mole fraction (to the oil) to achieve a decent reduction of the water-oil IFT. This study can provide a molecular level reference for implementing the CO2-EOR in the oil field under a low-pressure condition.

This work applied molecular dynamics (MD) simulation to calculate densities of natural gas mixtures at extremely high pressure (> 138 MPa) and high temperature (> 200 °C) conditions (xHPHT) to bridge the knowledge and technical gaps between experiments and classical theories. The experimental data are scarce at these conditions which are also out of assumptions for classical predictive correlations, such as the Dranchuk & Abou-Kassem (DAK) equation of state (EOS). Force fields of natural gas components were carefully chosen from literatures and the simulation results are validated with experimental data. The largest relative error is 2.67% for pure hydrocarbons, 2.99% for C1/C3 mixture, 7.85% for C1/C4 mixture, and 8.47% for pure H2S. These satisfactory predictions demonstrate that the MD simulation approach is reliable to predict natural- and acid-gases thermodynamic properties. The validated model is further used to generate data for the study of the EOS with pressure up to 276 MPa and temperature up to 573 K. Our results also reveal that the Dranchuk & Abou-Kassem (DAK) EOS is capable of predicting natural gas compressibility to a satisfactory accuracy at xHPHT conditions, which extends the confidence range of the DAK EOS.

With the increasing development of smart well technology in the oil and gas industry, there is a need for robust and reliable downhole power supply in order to provide stable power for downhole sensors and control tools. Usually, the produced fluid from the reservoir carries abundant thermal energy, which can be converted to electric power with thermoelectric technology. To realize in-situ power generation in the downhole environment, the design of downhole segmented concentric cylindrical thermoelectric generators (CCTEGs) with a cold fluid is proposed. A mathematical model for downhole thermoelectric generation is presented, which considers the heat transfer in the interior of thermoelectric element and from surrounding formation. The power performance in an oil well with 50% of water cut is investigated by using an engineering equation solver program. Numerical results show that about 800 W of power output could be obtained with 200 m length of segmented CCTEG, which is enough to provide power for typical downhole applications. The length of the segmented CCTEG and the injection rate of cold fluid dominantly affect the power output. The power consumption requirement for downhole applications in different operation periods could be met by simply adjust the injection rate of cold fluid.

Sour gas reservoirs have faced critics for environmental concerns and hazards, necessitating a novel outlook to how the produced sour gases could be either utilized or carefully disposed. Over the years of research and practice, several methods of sour gas processing and utilization have been developed, from the solid storage of sulfur to reinjecting the sour gas into producing or depleted light oil reservoir for miscible flooding enhanced oil recovery. This paper seeks to investigate the impact of injection parameters on the performance of sour gas injection for enhance oil recovery. In designing a miscible gas flooding project, empirical correlations are used and the key parameter which impacts the phase behavior is identified to be the minimum miscibility pressure (MMP). A compositional simulator was utilized in this research work to study the effect of injection parameters such as minimum miscibility pressure, acid gas concentration, injection pressure and injection rate on the performance of miscible sour gas injection for enhanced oil recovery. The findings showed that methane concentration had a significant impact on the MMP of the process. Additionally, an increase in acid gas concentration decreases the MMP of the process as a result of an increase in gas viscosity, consequently extending the plateau period resulting in late gas breakthrough and increased overall recovery of the process.

The success of supercritical CO2 Enhanced Oil Recovery (EOR) cannot be duplicated if the cost of CO2 transposition and processing becomes prohibitive. Research results of the in-situ CO2 EOR (ICE) approach offered a potential technology for many waterflooded stripper wells that lack access to affordable CO2 sources. Previously the ICE synergetic mechanisms were only qualitatively attributed to oil swelling and viscosity reduction due to the preferential partition of CO2 into the oleic phase. This study aims to quantify the contributions to recovery factors from several plausible mechanisms with numerical modeling and simulation. First, the urea reaction was modeled as the CO2 generating chemical decomposing to CO2 and ammonia in the reservoir conditions. The CO2 partitions into oil, which leads to the reaction continuation to generate more CO2. The resulting ammonia largely left in water may further react with certain crudes to generate surfactants, thus, decrease the oil/water interfacial tension (IFT). It is expected that the oil containing CO2 also has a lower IFT with water. The reaction kinetics under different temperatures were incorporated into the numerical model. A numerical model featuring the synergetic mechanisms was built including stoichiometry and kinetics of urea reaction, oil swelling effect, oil viscosity reduction, and IFT reduction effect on the relative permeabilities. The laboratory experiments, pore volume injection versus oil saturation were history matched for three different oils including Dodecane, Earlsboro oil, and DeepStar oil. The phase behavior was modeled with the equation of state (EOS) under different mole fractions of CO2. The reaction kinetics were also modified to history match the laboratory experiment. The estimated reduction of oil viscosity was calculated, 76% for Earlsboro oil, 91% in DeepStar oil, and 75% in dodecane oil. The oil swelling factors ranged from 1.60% to 19% in the three lab models, which translates to the recovery factor of oil. The endpoints of relative permeability were modified to account for the recovery contribution to the IFT and viscosity reduction. The impact of reaction kinetics on oil swelling and recovery factor was also determined, and they are not numerically close to reaction kinetics used in the lab cases. The matched reaction kinetics, activation energy and reaction frequency factor for the dodecane laboratory experiment were 91.80 kJ/gmol and 6.5E+09 min−1. The study concluded that the incremental recovery due to oil swelling ranges between 3.16% and 18.30%, and then from 12.91% to 41.59% is due to IFT reduction for all the cases. The relative permeability and urea reaction kinetics remained the most uncertain parameters during history matching and modeling the ICE synergetic mechanisms.

Mineral precipitation or scale formation in reservoirs, injection, and production wells is recognized as an obstacle for hydrocarbon recovery. Significant production drops and injection losses can occur as a result of mineral precipitations during water flooding. Several attempts have been made to better understand the underlying mechanisms of mineral precipitation through experimental and numerical simulation studies. In this study, we have investigated the impact of mineral precipitation on oil recovery and injection performance of a synthetic reservoir through numerical simulations. Additionally, we studied the scaling (scale formation) tendency and precipitation amount of various minerals in wellbore based on water compositions from the Gulf of Mexico. We also studied the impact of mineral precipitation on water flooding efficiency by analyzing saturation profiles of the injected water. Our results indicate that the reservoir experiences severe damage with respect to ultimate recovery, and injectivity loss due to the scale formation. Water saturation profiles reveal that mineral precipitation in reservoirs not only leads to non-ideal displacement of the in-situ hydrocarbon, but also causes earlier water breakthrough. The results of mineral precipitation in wellbore show that while some minerals (e.g., calcite) precipitate in large amounts, other minerals (e.g., gypsum) remain in equilibrium with the flowing brine in wellbore under the same pressure and temperature conditions.

Marcellus Shale gas development brings significant economic impact to the United States and local areas. However, potential negative impacts on health, safety, and environment also draw public atte...

Hydraulic fracturing induces the shear failure of natural fracture which contributes to complex fracture network. The magnitude of fracture slip potentially causes some undesirable consequences including wellbore instability, casing deformation and fault reactivation. Therefore, it is important to predict the fracture slip induced by hydraulic fracturing for a safe and efficient stimulation. In this paper, we used a 2D hydro-mechanical coupled model to predict the injection-induced slip. The hydraulic and natural fractures are embedded in formations with cohesive zone model. The fracture propagation, rock deformation and wellbore slip displacement are captured in the 2D model. The wellbore slip displacement is input into a small-scale 3D mechanical model of casing in slip rock to simulate casing behavior. Casing curvature is also introduced to assess casing integrity. Results indicate that the rock deforms asymmetrically with respect to the wellbore after the shear failure of natural fracture. Particularly, there is a shear slip along the natural fracture. The simulation result shows that the casing failure mechanism is shear deformation induced by the fracture slip during hydraulic fracturing. The curvature of deformed casing is larger than that of directional well trajectory. The predicted results are validated by the logging and operation data from the field. This work provides a novel quantitative method for predicting fracture slip and evaluating well integrity during hydraulic fracturing.

Synergistic development of energy by combining geothermal and hydrocarbon gains an increasing attention. In practice, hydrocarbon reservoir fluids produced from oil and gas wells are used for electricity generation through a binary cycle power plant. To enhance the thermal recovery efficiency, we present an innovative design of in-situ geothermal power generation and illustrate a promising method of geothermal energy utilization in a cost-effective and environmentally friendly manner. This proposed design is an integration of thermoelectric generation technology, well completion and production operation. In this design, electricity is generated downhole by thermoelectric generators (TEG) installed on the outer side of the production string to convert the thermal energy to electric power. Heat transfer model is set up to determine the temperature field with a case study to demonstrate the downhole power generation efficiency. The results are compared with both simulation and experiment results. The proposed design capitalizes on existing hydrocarbon production wells and retrofit them for power generation. This practice can be a great complementary for surface power plants, and could reduce operational cost and extend the economic lifetime of oil and gas wells, especially for high water-cut wells in mature fields.

Hydraulic fracturing enables the commercial development of unconventional resources in shales and tight formations. The conductivity and complexity of created fractures are critically dependent on the rheology of fracking fluid and the mechanics properties of rocks. Literatures show that both the rheology of fracturing fluid and fracture propagation dynamics are affected by the temperature of fracturing fluid. Neglecting the temperature transient behaviour may defeat the purpose of fracturing optimization during fracture initiation, propagation, and sand packing. The objective of this paper is to investigate the impact of temperature on fracturing design by studying the transient temperature behaviour across a complex wellbore using numerical modelling by coupling a finite difference heat transfer model with a dynamic fracture propagation model. The study results show that with the injection of cold fracturing fluid, hydraulic fracture propagation is decelerated, and production prediction is thus lessened compared with the case ignoring temperature effect. For multistage fractured wells, fracture geometry enlarges along the fluid flow direction in a horizontal segment. This potentially lowers the cost of hydraulic fracturing designs.

Hydraulic Fracturing (HF) is a frequently used well stimulation technology to improve a well's productivity by increasing the contact area with the formation matrix. Hydraulic fractures are created by following a customized design based on imperfect knowledge of the subsurface formation and idealizations. Therefore, the resulting fracture system is often different from the original design, which calls for post-fracturing evaluations. Fracture diagnostics are utilized to understand fracture behavior during or after hydraulic fracturing. Understanding the geomechanics of how fractures form during fracturing has been studied in detail; however, predicting fracture genesis and propagation behavior has been a challenging endeavor because of reservoir heterogeneity. This paper will reveal the current fracture diagnostic technologies and assess their ability to detect HF extension and quantify the properties of hydraulic fractures in terms of conductivity and stimulated reservoir volumes. This paper is not an abridged version of the technical manual regarding how each method is conducted or used but focuses on insight into what they measure and their difference from others. With the critical reviews on current HF diagnostic technologies, we intend to (1) define key terminologies that are often used in HF evaluation to set up a common linguistic lexicon for comparison, (2) provide a brief discussion on their mechanisms; (3) stipulate a framework on how to choose proper HF diagnostic tools and analysis methods for different HF applications.

The wellbore integrity plays an important role in petroleum operations like drilling, well completion and production. Caliper, Electrical image logs, Acoustic televiewers (ATV) and Optical televiewers (OTV) are some of the devices currently used in the industries to identify breakouts. However, these techniques are restricted in applications. For instance, caliper sometimes indicates the effect of drill spiral grooves as borehole enlargement zones; poor resolution and complicated processing procedure limit the application of the electrical image logs. The ATV and OTV which give better outputs are not often used due to the high cost of installation and operation. These limitations necessitated a new approach to quantifying the wellbore instability. This research work focuses on data analytics and the development of the Bayesian Algorithm (with code in Python) to predict the wellbore failure probability using real-time pore pressure and fracture gradients data obtained from the wellbore using modified d-exponent.

By the nature of reliability, sustainability, abundant resource and minor impact on environment, geothermal energy is considered as one of the future resources to meet the world's growing energy demand. Harnessing geothermal energy from oil wells by existing assets, data and technologies features significant advantages over traditional geothermal wells, especially in reduced capital expenditure and operational risks. To raise awareness and promote discussions on oilfield geothermal development, this paper comprehensively characterized the oilfield associated geothermal resource, reviewed the current geothermal development in worldwide oilfields, pinpointed the existing challenges and introduced multidisciplinary technologies as possible solutions to unlock the potential and promote extensive development of geothermal energy from oilfields. Moreover, an integrated risk/opportunity assessment and management framework is proposed to improve the outcomes of diverse oilfield geothermal projects in practice.

In-situ combustion is often used to develop heavy oil as it has multiple advantages over alternative thermal methods. However, the wellbore integrity can be compromised if the casing is not properly designed or manufactured. Based on the fundamentals of heat transfer, a mathematical model with multiphysics is built to study the temperature and pressure distributions surrounding the wellbore during in-situ combustion. In laboratory, real casings and coupons with grades of N80, P110, and 3Cr110 were tested under high temperature to study their mechanical performances in the in-situ combustion recovery. From the modeling and laboratory testing results, we propose the casing design and manufacture protocols for thermal recovery of heavy oil. Field applications in Liaohe oil field, Du-66 Block, shows that the mechanical deterioration of P110 and 3Cr110 is less than that of N80 and the mechanical performance stability of 3Cr110 is better than others when the temperature is less than 600 ° C . When the temperature is above 600 ° C for more than 10 h, the mechanical performance of all casing grades declines quickly. Applying finite element analysis, we recommend a safety factor of 1.1 for designing casing at the temperatures of 250 °C,480 °C and 485 °C. The finding of this study provides fundamentals for the casing design and material selection for in-situ combustion recovery.

Summary The single-well chemical-tracer test (SWCTT) has been applied for decades with much success in estimating residual oil saturation in near-wellbore locations. The information obtained from an SWCTT is critical for designing a method for enhanced oil recovery (EOR). However, a key assumption in the conventional SWCTT is that only single-phase (water) is mobile. In reality, this is often not the case, and significant error can occur if the conventional SWCTT analysis method is used when multiple phases flow at the same time. The objective of this study is to improve the accuracy and precision of SWCTT interpretation in a multiphase-flow condition. In this paper, we propose an innovative procedure of SWCTT and modify the method of moment (MOM), aiming at the two-mobile-phase condition. In the development of the algorithm, a ratio parameter is introduced to adjust the calculated swept-volume difference between the conservative tracer and the partitioning tracer. In addition, a mixture injection of oil and water is required, instead of the pure-water injection in an SWCTT. The proposed approach is verified through numerical simulation on synthetic cases with known input parameters. The model being simulated consists of a radial-flow regime with a single vertical well in the center. The input oil saturation varies from 0.1 (immobile oil saturation) to 0.9. Our results show that the saturation estimated from the modified MOM matched the simulation input data, indicating that our approach is able to capture the saturations under two-mobile-phase condition. Moreover, the modified MOM can also be applied in single-mobile-phase condition and can improve the accuracy of conventional MOM.

Casing failure during hydraulic fracturing is infrequent, but its consequence and impact can be significant for the shale gas wells. It may result in inaccessible cased hole and environmental and safety concerns over wellbore integrity during the shale gas reservoir development. Based on theoretical analysis, numerical simulation and field measurement, the failure mechanisms of casings in shale gas wells are revealed. Through parametric sensitivity analysis, the countermeasures are recommended. Results indicate that one of the casing failure mechanisms in shale gas wells is shear deformation induced by the slip of shear fractures. The simulated casing deformation is consistent with the lead impression. Casing curvature is introduced to assess the traveling capability and casing integrity. The maximum curvature is significantly larger than that of normal directional borehole, which causes the resistance of downhole tools passing through casing. Decreasing the crossing angle and employing the cement with a low Young's modulus or even no cementing can be the effective measures to prevent casing failure in this mode. The research findings provide new evaluation criterion and controlling methods for casing integrity in shale gas wells under hydraulic fracturing.

The density distribution of hydrocarbon molecules in Nano-pore media affects the storage of gas, particular for shale reservoir which contains rich organic matters. The density distribution can reveal the adsorption effect which is related to the gas storage mechanism. In literature, researchers proposed using local density theory such as Lennard Jones Potential in lieu of molecular dynamics (MD) simulation and laboratory measurement because of its high computation performance. Core sample study shows that many pores in organic matter have cylindrical shape, but the curvature effect on gas storage has not been studied. Therefore, the thorough validation of this approximation needs to be done for different pore geometries, particularly for a multiple components system. In this study, we propose to study the shale gas storage under the reservoir conditions by a thorough comparison between the Lennard Jones Potential with Peng-Robinson EoS (LJ-PREOS) and equilibrium molecular dynamics simulation for cylindrical pores. We first compare the LJ-PREOS for a single component, and then extend the study to a binary system. The purpose of this comparison to quantify the boundaries under which the LJ-PREOS can be used as a proxy to study the gas storage and adsorption effect in shale formation. After Comparing the results from equilibrium MD simulation with new SLD-PR model, for the single component system, the density on the both sides (close to the pore wall) is much higher than the density on the center, which means the cylindrical wall has a significant adsorption effect on methane molecule. For the binary component system, the mixture density distribution is similar to the single component system, which is higher density closer to the wall and lower density on the center. Furthermore, from the MD simulation results, for the density distribution of each single component in binary system, it is clearly show that both components are still under adsorption effect from the wall, but the butane molecule largely concentrate close to the edge of pore, which means the cylindrical wall has larger impact on butane molecule than methane molecule. With the validated model, we developed a framework to estimate the gas storage capacity of the organic matters in shale formation with different pore size distributions (PSD). Neglecting PSD may lead to 30% under estimation of gas storage in shale gas formation. To our knowledge, this is first validation of cylindrical pore adsorption for a multiple components system using MD modeling even though many researchers have used this hypothesis in their studies. We also proposed a new framework of estimating gas storage capacity in shale formation without distinguishing the adsorption and free gases in the organic pores with the effect of pore size distribution.

Thermal cracking in reservoir rocks can result in significant changes in transport properties. Siltstone, limestone, and conglomerate samples taken from oil-bearing formations were heated to a range of peak temperatures up to 800 °C at ambient pressure. Porosity and gas permeability were measured. Changes in rock microstructures were observed using scanning electron microscopy (SEM). The results show the strong effect of thermal cracking on gas permeability and porosity. Different rock types have different thermal cracking threshold temperatures. Above the threshold temperature, crack widths and lengths are increased and a crack network is well-developed, resulting in sharp variations in gas permeability and porosity. In order to understand the factors that influence both thermal cracking and gas permeability changes in rock, a mathematical model based on fracture mechanics theory and thermoelasticity theory is proposed to describe how permeability changes with increases in temperature. The proposed permeability model was validated using experimental data. The results from the proposed model indicate that thermal cracking and permeability changes are mainly driven by the difference between mineral thermal expansion coefficients. Below the temperature that causes mineral decomposition, the temperature-driven permeability change obtained from the proposed model is in good agreement with our experimental results.

Summary An oil field in Xinjiang, China, experienced a casing failure rate of 15 to 30% in thermal wells, mainly relating to inadequate protocols of casing design. This paper presents a new strain-based casing-design method. New material parameters are proposed to build safety-evaluation principles throughout the service life of a thermal well. In addition, a gas-tight thread joint is applied to prevent steam leakage that otherwise would cause a large transversal stress between different formations, and result in slip deformation of the casing string. Field practices have shown that the new method's fitness works better for thermal wells than previously used methods.

Less than 10% of oil is usually recovered from liquid-rich shales and this leaves much room for improvement, while water injection into shale formation is virtually impossible because of the extremely low permeability of the formation matrix. Injecting carbon dioxide (CO2) into oil shale formations can potentially improve oil recovery. Furthermore, the large surface area in organic-rich shale could permanently store CO2 without jeopardizing the formation integrity. This work is a mechanism study of evaluating the effectiveness of CO2-enhanced oil shale recovery and shale formation CO2 sequestration capacity using numerical simulation. Petrophysical and fluid properties similar to the Bakken Formation are used to set up the base model for simulation. Result shows that the CO2 injection could increase the oil recovery factor from 7.4% to 53%. In addition, petrophysical characteristics such as in situ stress changes and presence of a natural fracture network in the shale formation are proven to have impacts on subsurface CO2 flow. A response surface modeling approach was applied to investigate the interaction between parameters and generate a proxy model for optimizing oil recovery and CO2 injectivity.

Shale gas development in the Sichuan-Chongqing region in China has experienced a high level of casing deformation or failure during hydraulic fracturing treatment, which has resulted in significant productivity decline and economic losses. This problem has motivated many studies in the literature but focusing on the shearing deformation using the finite element method. This paper categorizes the casing failure modes and mechanisms in the region and presents casing collapse laboratory results. The designed laboratory tests rendered us critical data points in casing deformation under different loading scenarios. For multiple stage hydraulic wells in the region, we propose to use a strain-based protocol for casing design instead of the current design based on maximum stress.

Water flooding is the most widely used improved oil recovery technique, and many other methods, such as chemical methods, are based on water flooding performance. If the injected water is not compatible with the formation water, scaling and other solid deposition would occur, which can reduce the formation permeability and transmissibility of the reservoir. The objective of this research is to model the in-depth reservoir formation damage as a result of scaling and to simulate its impact on reservoir performance. Literature survey shows that the development of a theoretical model for estimation of permeability and porosity reduction is of practical importance. In this paper, two models based on barium concentration were proposed to estimate permeability reduction in porous media as a result of scale deposition. Model development was conducted by using 216 experimental data points from literature covering various thermodynamic properties and reservoir conditions, and statistical and graphical error analyses were employed to evaluate the accuracy of the proposed models. The results showed that the proposed models are capable of predicting permeability alteration caused by scale deposition with absolute average relative errors less than 1% compared with the experimental data. In addition, the values of root mean square error and coefficient of determination were found to be nearly 0.1 and 0.95 for the high barium concentration model and 0.06 and 0.94 for the normal barium concentration model. Moreover, error distribution curves of the developed models showed that the models do not have any significant error trend under different reservoir and thermodynamic conditions. A synthetic field was used to simulate the injection and production performance of an incompatible water flooding operation to better study the impact of scaling issue on reservoir performance. In particular, the impacts of scale deposition on reservoir properties and injection pressure were investigated. The results of numerical simulation indicated that scale formation could reduce the reservoir porosity from 0.2 to nearly 0.07. Moreover, the injection bottom hole pressure needed for the operation increases significantly up to nearly 19,000 psi when the reservoir is affected by scale formation.

The well performance in Coal-Bed Methane (CBM) reservoir is highly dependent on the conductivity of hydraulic fracture created to increase well production rate and contact area with the reservoir. Aimed at improving the effective fracture length of hydraulic fracture in CBM reservoir and the seam proppant concentration, the objective of this paper is to investigate the migration of variable density proppant particles in hydraulic fracture and seams using numerical modeling and simulation. In the proposed model, the interaction among fracture proppant particles distributed in a pseudo fluid model is taken into consideration. Comparison between the model calculation and field radioactive tracing logging interpretation shows that the proposed model is accurate and reliable in applications. Additionally, we carried out the sensitivity study on the viscosity of fracking fluid, fracture area, proppant density, injection rate and other factors. It is shown that, with the condition of a confining pressure of 69 MPa and an ambient temperature of 90 °C, the crush value of nutshell proppant is less than 2%, which meets the field application requirements. Furthermore, with the increase of both fracturing fluid viscosity and injection rate, the propped effective fracture length increases, and lead to a more uniform distribution of proppants. The increase in proppant particle diameter, inversely, results in a decrease in the effective fracture length. As for variable-density proppant, the effective crack support length would be longer than the single ceramic proppant, and the particle distribution of the case with variable density is more uniform.

Summary On the basis of the wellbore and reservoir heat-transfer process during deepwater drilling, a heat-transfer model between wellbore and formation is built up for two different conditions: without riser and with riser. Wellbore and formation temperature distributions under different drilling-fluid-injection temperatures, flow rates, circulating times, and drilling depths are simulated by use of this model. Taking the hydrate-phase equilibrium into consideration, a possible region of hydrate-formation dissociation is analyzed, and effective methods are proposed to control the hydrate dissociation. The results indicate that, during shallow formation drilling, the increase of drilling-fluid flow rate will cause the wellbore temperature to rise, but below the hydrate-dissociation temperature in the whole process; during deep-formation drilling, drilling fluid is heated, and the heat is transferred from the deeper formation to the shallower formation through fluid circulation. Thus, the hydrate-reservoir temperature increases gradually along the wellbore radial direction. Hydrates will dissociate after the hydrate equilibrium temperature is reached; this may cause wellbore collapse or methane leak from the reservoir and result in disaster. To control hydrate dissociation during deepwater drilling, attention should be paid to the period of deep-formation drilling. Sensitivity studies indicate that the risk of hydrate dissociation rises as the drilling-fluid-injection temperature, flow rate, and circulating time increase.

Oil production decline and excessive water production are prevalent in mature fields and unconventional plays, which significantly impact the profitability of the wells and result in costly water treatment and disposal. To seek for a sustainable development of those wells, reducing the operation cost and extending their economic lives, this paper presents a method of synergistic production of hydrocarbon and electricity, which could harvest the unexploited geothermal energy from the produced water and transfer heat to electricity in the wellbore. Such method is cost-effective, since it does not require any surface power plant facility, and it is replicable in numerous wells including both vertical wells and horizontal wells. By simultaneous coproduction of oil and electricity, the value of existing assets could be fully developed, operation cost could be offset, and the economic life of the well could be extended. This recently proposed method incorporated thermoelectric power generation technology and oil production. In this method, electricity could be produced by thermoelectric generator (TEG) mounted outside of the tubing wall under temperature gradient created by produced fluid and injected fluids. The aim of this paper is to illustrate the economic practicability of oil-electricity coproduction by using thermoelectric technology in oil wells based on previously proposed design. We examined the technical data of high water-cut oil wells in North Dakota and collected required information with respect to performance thermoelectric power generations. Special emphasis was placed on the key parameters related to project economics, such as thermoelectric material, length of TEG and injection rate. Sensitive studies were carried out to characterize the impact of the key parameters on project profits. We showed that by simultaneously production of oil and electricity, $234,480 of additional value could be generated without interfering with oil production. The proposed method capitalizes on the unexploited value of produced water and generates additional benefits. This study could provide a workflow for oil and gas operators to evaluate an oil-electricity coproduction project and could act as a guidance to perform and commercialize such project to balance parts of the operation cost and extend the life of the existing assets.

Due to the layered texture and sedimentation environment, shale formations usually characterized as high heterogeneity and anisotropy in in-situ stresses. During the hydraulic fracturing process, fracturing fluid is injected at a pressure above the formation pressure. This injection process changes the local in-situ stresses in a quick and significant manner while generating fracture systems. In the regions of existing geo-features such as natural fractures and faults, local stress changes could lead to the activation of formation movement, which in return impacts the casing going through the locale. Casing deformations during hydraulic fracturing have been observed in Southwest China Sichuan basin, and it have impeded completion operations in certain regions. In order to ensure further exploring, we analyszed this phenomenon and propose practical solutions for fault reactivation prevention. To study the mechanism of local slippage and the impact on casing integrity, we set up a 2D finite element model with considerations of in-situ stresses acquired from fields, natural fracture orientation from available seismic data, and we simulated water injection process in order to quantify potential slippage and displacement. The finite element model features an integration of casing, cementing, and formation under the hydraulic fracturing conditions. For particular parameters such as permeability and leak-off coefficeint, we conducted sensitivity studies to quantify their impacts on displacement amount. The theoretical geomechanics studies indicate water induced slippage existence in shale due to its fracture reactivation. Using the finite element model, this paper interpreted and quantified the impact of fracturing fluid injection on casing from strike-slip fault regiems. Simulation results revealed that water injection into natural fractured shale formation can induce finite displacement characterized as fault slippage along discontinues surfaces. This study could help engineers to have a better prediction as how hydraulic fracture intereact with subsurface structures and potential risks that comes along with it. This type of casing damage can be reduced by improving well trajectory design, completion operation, and higher strength level of casing-cement system. The findings from this study not only can be applied to naturally fractured formations, but also to other pre-existing geo-features such as discountinues surfaces. It also provides fundamental basis for more practical solution to find the measures and overcome the casing deformation problems in hydraulic fracturing.

In recent years, the exploration and production of oil and gas from Bakken formation in Williston Basin have proceeded quickly due to the application of multi-stage fracturing technology in horizontal wells. Knowledge of the rock elastic moduli is important for the horizontal drilling and hydraulic fracturing. Although static moduli obtained by tri-axial compression test are accurate, the procedures are cost expensive and time consuming. Therefore, developing correlation to predict static moduli from dynamic moduli, which is calculated from sonic wave velocities, is meaningful in cutting cost and it makes the unconventional oil and gas exploration and production more efficient. Literature review indicates such a correlation is not available for Bakken formation. This may be attributed to the extremely low success rate in Bakken core sample preparation and not enough published data to develop correlation to relate dynamic moduli to static moduli. This study measures and compares the moduli obtained from sonic wave velocity tests with deformation tests (tri-axial compression tests) for the samples taken from Bakken formation of Williston Basin, North Dakota, USA. The results show that the dynamic moduli of Bakken samples are considerably different from the static moduli measured by tri-axial compression tests. Correlations are developed based on the static and dynamic moduli of 117 Bakken core samples. The cores used in this study were taken from the core areas of Bakken formation in Williston Basin. Therefore, they are representatives of the Bakken reservoir rock. These correlations can be used to evaluate the uncertainty of Bakken formation elastic moduli estimated from the seismic and/or well log data and adjust to static moduli at a lower cost comparing with conducting static tests. The correlations are crucial to understand the rock geomechanical properties and forecast reservoir performance when no core sample is available for direct measurement of static moduli.