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.
Temizel, Cenk (Aera Energy) | Balaji, Karthik (University of North Dakota) | Canbaz, Celal Hakan (Ege University) | Palabiyik, Yildiray (Istanbul Technical University) | Moreno, Raul (Smart Recovery) | Rabiei, Minou (University of North Dakota) | Zhou, Zifu (University of North Dakota) | Ranjith, Rahul (Far Technologies)
Due to complex characteristics of shale reservoirs, data-driven techniques offer fast and practical solutions in optimization and better management of shale assets. Developments in data-driven techniques enable robust analysis of not only the primary depletion mechanisms, but also the enhanced oil recovery in unconventionals such as natural gas injection. This study provides a comprehensive background on application of data-driven methods in oil and gas industry, the process, methodology and learnings along with examples of data-driven analysis of natural gas injection in shale oil reservoirs through the use of publicly-available data.
Data is obtained and organized. Patterns in production data are analyzed using data-driven methods to understand key parameters in the recovery process as well as the optimum operational strategies to improve recovery. The complete process is illustrated step-by-step for clarity and to serve as a practical guide for readers. This study also provides information on what other alternative physics-based evaluation methods will be able to offer in the current conditions of data availability and the understanding of physics of recovery in shale oil assets together with the comparison of outcomes of those methods with respect to the data-driven methods. Thereby, a thorough comparison of physics-based and data-driven methods, their advantages, drawbacks and challenges are provided.
It has been observed that data organization and filtering takes significant time before application of the actual data-driven method, yet data-driven methods serve as a practical solution in fields that are mature enough to bear data for analysis as long as the methodology is carefully applied. The advantages, challenges and associated risks of using data-driven methods are also included. The results of comparison between physics-based methods and data-driven methods illustrate the advantages and disadvantages of each method while providing the differences in evaluation and outcome along with a guideline for when to use what kind of strategy and evaluation in an asset.
A comprehensive understanding of the interactions between key components of the formation and the way various elements of an EOR process impact these interactions, is of paramount importance. Among the few existing studies on natural gas injection in shale oil with the use of data-driven methods in oil and gas industry include a comparative approach including the physics-based methods but lack the interrelationship between physics-based and data-driven methods as a complementary and a competitor within the era of rise of unconventionals. This study closes the gap and serves as an up-to-date reference for industry professionals.
Paul, Ferm (Nouryon) | Jeff, Germer (Nouryon) | Kurt, Heidemann (Nouryon) | Stuart, Holt (Nouryon) | Andrew, Robertson (Nouryon) | Jannifer, Sanders (Nouryon) | Klin, Rodrigues (Nouryon) | John, Thomaides (Nouryon) | Nick, Wolf (Nouryon) | Lei, Zhang (Nouryon)
The controlled release of scale inhibitors (SI) and other treatment chemicals in the near-wellbore region is a key strategy to improving water management and extended well production. In addition, during some completion and stimulation operations, it is desired that robust particles providing controlled release be placed in gravel and sand packs. A novel controlled release scale inhibitor particle is presented which provides beneficial properties due to its unique chemistry and polymer processing methods. This technology provides extended feedback of scale inhibitor with tunable release rates.
Steam-Assisted Gravity Drainage (SAGD) is one of the popular methods for heavy oil production. The process is efficient and economical. However, it requires the use of large quantity of water and disposal of waste water can be costly. In addition, burning of natural gas for steam generation contributes to additional carbon dioxide generation, a known greenhouse gas, which is also undesirable. A method to heat up the in-situ oil without the use of injected water is highly desirable. Radio frequency (RF) heating of heavy oil reservoir is a potential method for oil recovery without steam injection. The evaluation of the potential of such method requires the coupling of a reservoir simulator with an electromagnetic (EM) simulator.
This paper describes the development and implementation of a flexible interface in a reservoir simulator that allows the runtime loading of third party software libraries with additional physics. Data is exchanged between the reservoir simulator and externally loaded software libraries through memory, therefore there is minimal communication overhead. The implementation allows for iterative coupling, explicit coupling and periodic coupling. This paper describes the mathematical coupling of the mass and energy conservation equations in the reservoir simulator with the Maxwell equations in an external library. The electromagnetic properties in the reservoir are highly dependent on temperature and water saturation, this dependence is accounted for in the coupled code using table look-up properties.
Canadian heavy oil and reservoir properties were used in our simulation investigation. We found that RF heating alone can be effective in heating up the in-situ water and reducing heavy oil viscosity by several orders of magnitude. As the in-situ water near wellbore was vaporized by RF heating, electrical conductivities were reduced to zero and thus allowed the EM wave to propagate further into the formation and heat up the water further away from the wellbore. With properly designed RF heating field pilots and tuning of EM and reservoir parameters, the coupled reservoir/EM simulator can be a powerful tool for the evaluation and optimization of RF heating operations.
The interface is sufficiently flexible to allow different types of multi-physics coupling. In addition to RF heating, it has also been used for reaction kinetics and geomechanics coupling with a reservoir simulator. It has been used for large scale coupled full field simulation with over 30 million cells.
Production from highly paraffinic crude oil wells poses unique technical challenges such as poor flowability and paraffin deposition on the production tubing. Paraffin deposition increases the lift load on the pump, reduces pump efficiency, and eventually plugs the pump. To restore the productivity of these wells a common solution is to inject hot oil or hot water at 160°F–200°F to clean the deposits. This process imposes higher operating cost and lost production due to well downtime.
Paraffin inhibitor (PI) and pour point depressant (PPD) have been used to treat paraffinic fluids but are not effective for wells with high water cuts. These wells when treated with PI/PPD still require high cost maintenance such as the hot oil/water jobs and/or well workover. This paper presents a more effective treatment using tailored chemical mixtures to form a water dispersion with the paraffinic oil, thus to increase oil flowability and reduce deposition. A novel test method has been developed to evaluate effectiveness of treatment chemicals on various paraffinic oils based on flowability and cleanliness. The test method has been validated with field trial data from three different wells in the Uinta Basin, Utah and Julesburg Basin, Colorado.
The results of the field trials showed a significant increase in pumping efficiency and crude oil production. Need for hot water application was also reduced or eliminated for the treated wells. Improved oil and produced water quality were also observed. These results demonstrated that the water dispersion-based treatment is a more effective treatment for high paraffin wells with high water cuts.
A major shale producer in North America with established oil and gas production was facing challenges with severe paraffin deposition in downhole tubing and flowlines. Since chemical recommendations based on traditional screenings failed to deliver adequate inhibition, the operator turned to a costly remediation program to maintain production. We aimed to revisit the case, do a root cause analysis, and look for a potential chemical solution for cost savings. The field deposit obtained from the producer proved to be quite complex and introduced limitations with our current internal HTGC method for carbon chain analysis. Upon analysis, components present in the sample were found to exceed the solidity limits of the carrier system, carbon disulfide (CS2) and would precipitate out of the solution and form a two-phased system. These components were believed to be higher molecular weight carbon chains (HMWC) above C70+ at a high enough concentration to exceed the solvents solubility limit. This was the first time encountering such a sample in our experience. A systematic approach was applied to isolate the insoluble HMWC and further outsourced analysis. A MALDI-TOF and High-Resolution Carbon-13 NMR was utilized to confirm the presence of C90+ chains within the deposit at a high enough concentration to have a trimodal paraffin distribution system. To our knowledge, this is the first time a trimodal system has been documented.
Reliable estimation of organic matter characteristics is essential in drilling decisions, source rock evaluation, and unconventional reservoir production. Their measurement is based on experiments after core sampling, which is time-consuming and economically challenging. In this study, we present a new approach to evaluate the characteristics of organic matter in source and reservoir rocks by in-situ electrical heating and temperature transient analysis under in-situ conditions.
The new approach is based on inverse modeling, which monitors in-situ heater temperature during electrical heating and machine learning technologies. Thermal method of electrical heating is applied for the in-situ pyrolysis, to figure out the characteristics of organic matter—kerogen volume fraction and activation energy of decomposition reaction. The heater temperature acts as an indicator of type and maturity of kerogen, since it is affected by the bulk thermal conductivity of formation, which is a function of dynamically changing rock-and-pore composition by kerogen decomposition. A full-physics simulation model of in-situ kerogen pyrolysis is used to generate output data of electrical heater temperature, which is the input data of learning-based models. Minimal simplification of physical and chemical phenomena in the full-physics simulation model, which describes the multicomponent-multiphase-nonisothermal systems involving kinetic reactions, gives the confidence of synthetic output data of heater temperature.
Full-physics simulation model computes system responses under unknown and uncertain input parameters, which determine the reactivity of kerogen pyrolysis. The full-physics simulation model generates the sets of heater temperature transient data while heating with constant heat flux, in the 300 different simulated source rocks containing Types 1, 2, and 3 kerogens with various organic matter content and activation energies. Based on the set of heater temperature transient data as input parameters, Artificial Neural Network (ANN) is employed to generate a black box model to estimate the unknown organic matter content and activation energy. Developed ANN data-driven model shows better performance in estimating unknown parameters, in Types 2 and 3 kerogens with wide ranges of activation energies than Type 1 kerogen with a narrow range of activation energy. Support Vector Machines (SVM) method, which categorizes data into multiple classes by using hyperplanes, is applied to classify the heater temperature transient data into different types of kerogens and shows good performance in classification.
The new characterization technology of in-situ organic matter in source rocks presented in this study provides reliable information of types and maturity of organic matter, without experiments after core sampling. It is expected to enable the realistic evaluation of source rocks under subsurface conditions, by resolving technical and economic challenges.
Gaither Draw Unit is a heterogeneous and tight formation with an average permeability less than 0.1 mD. After more than 1.7 MMSTB water injection, there was no clear indication or benefit of the injected water from any producer. However, knowing the distribution of the injected water is critical for future well planning and quantifying the efficiency of injection. The objective of this study is to show how the Capacitance-Resistance Model (CRM) was used on this field and validated using other independent methods.
The CRM model describes the connectivity and the degree of fluid storage quantitatively between injectors and producers from production and injection rates. Rooted in material balance, signals from injectors to producers can be captured in the CRM. Using constrained nonlinear multivariable optimization techniques, the connectivity is estimated in the selected portion of the field through signal analysis on injection and production rates. In this tight formation, the whole field is divided into seven regions with one injection well and surrounding producers to conduct CRM analysis. We further use integrated but independent approaches to validate the results from CRM. The validation includes full field modeling and history match and fluid level measurement using echometering technology.
This paper focuses on a real field water flooding project in Gaither Draw Units(GDU). CRM is used to detect reservoir heterogeneity through quantifying communication between injectors and producers, and attains a production match. The fitting results of connectivity through CRM indicate permeability regional heterogeneity, which is consistent with full field modelling. The history matched full field model presents the saturation distribution showing that the majority of injected water mainly saturates the surrounding regions of injectors, and the low transmissibility slows down the pressure dissipation. Overall, the comprehensive interpretation obtained through these three independent methods is consistent, and is very useful in planning infill well drilling and future development plan for the Gaither Draw Units.
This paper shows that it is critical to integrate different sources of data in reservoir management through a field case study. The experience and observations from this asset can be applied to other tight formations being developed with water flooding projects.
Mudstone (shale) reservoir evaluation and efficient development poses a significant challenge due to the heterogeneous nature of these complex formations. Organic-rich shales are characterized by intricate mineralogy, ultra-low nanoporosity, and nano-darcy permeability making these tight source/reservoir rocks challenging in obtaining economically viable hydrocarbons. Consequently, characterizing and quantifying minerology and intra-/interparticle (non)organic-hosted porosity at the pore-scale, and up-scaling it to the core-scale remains a significant focus of evaluating reservoir quality in shale plays.
Current advances in correlative multi-scale and multi-modal 2D/3D imaging of nanoporous geomaterials, such as shales, provide a tremendous opportunity to characterize and represent these rocks over multiple length scales – from core-to pore-scale. Subsequently, these image datasets can be then used for advanced image analysis and digital rock modeling to reconstruct 2D/3D models used to analyze their petrophysical properties.
In this study, the Mancos Shale from the Uinta Basin – one of the most promising shale plays in the United States (
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.