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.
Wellbore instability is caused by the radical change in the mechanical strength as well as chemical and physical alterations when exposed to drilling fluids. A set of unexpected events associated with wellbore instability in shales account for more than 10% of drilling cost, which is estimated to one billion dollars per annum. Understanding shale-drilling fluid interaction plays a key role in minimizing drilling problems in unconventional resources. The need for efficient inhibitive drilling fluid system for drilling operations in unconventional resources is growing. This study analyzes different drilling fluid systems and their compatibility in unconventional drilling to improve wellbore stability.
A set of inhibitive drilling muds including cesium formate, potassium formate, and diesel-based mud were tested on shale samples with drilling concerns due to high-clay content. An innovative high-pressure high temperature (HPHT) drilling simulator set-up was used to test the mud systems. The results from the test provides reliable data that will be used to capture more effective drilling fluid systems for treating reactive shales and optimizing unconventional drilling.
This paper describes the use of an innovative drilling simulator for testing inhibitive mud systems for reactive shale. The effectiveness of inhibitive muds in high-clay shale was investigated. Their impact on a combination of problems, such high torque and drag, high friction factor, and lubricity was also assessed. Finally, the paper evaluates the sealing ability of some designed lost circulation material (LCM) muds in a high pressure high temperature environment.
The significant temperature difference between the fractured and non-fractured regions during the stimulation fluid flow-back period can be very useful for fracture diagnosis. The recent developments in downhole temperature monitoring systems open new possibilities to detect these temperature variations to perform production logging analyses. In this work, we derive a novel analytical solution to model the temperature signal associated with the shut-in during flow-back and production periods. The temperature behavior can infer the efficiency of each fracture. To obtain the analytical solution from an existing wellbore fluid energy balance equation, we use the Method of Characteristics with the input of a relevant thermal boundary condition. The temperature modeling results acquired from this analytical solution are validated against those from a finite element model for multiple cases.
Compared to the warm-back effect in the non-fractured region after shut-in, a less significant heating effect is observed in the fractured region because of the warmer fluid away from the perforation moving into the fracture (after-flow). Detailed parametric analyses are conducted on after-flow velocity and its variation, flowing, geothermal, and inflow temperature of each fracture, surrounding temperature field, and casing radius to investigate their impacts on the wellbore fluid temperature modeling results.
The inversion procedures characterize each fracture considering the exponential distribution of temperature based on the analytical solutions in fractured and non-fractured regions. Inflow fluid temperature, surrounding temperature field, and after-flow velocity of each fracture can be estimated from the measured temperature data, which present decent accuracies analyzing synthetic temperature signal. The outputs of this work can contribute to production logging, warm-back, and wellbore storage analyses to achieve successful fracture diagnostic.
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.
Alkinani, Husam H. (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb T. (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology) | Alkhamis, Mohammed M. (Missouri University of Science and Technology) | Mutar, Rusul A. (Ministry of Communications and Technology)
Lost circulation is a complicated problem to be predicted with conventional statistical tools. As the drilling environment is getting more complicated nowadays, more advanced techniques such as artificial neural networks (ANNs) are required to help to estimate mud losses prior to drilling. The aim of this work is to estimate mud losses for induced fractures formations prior to drilling to assist the drilling personnel in preparing remedies for this problem prior to entering the losses zone. Once the severity of losses is known, the key drilling parameters can be adjusted to avoid or at least mitigate losses as a proactive approach.
Lost circulation data were extracted from over 1500 wells drilled worldwide. The data were divided into three sets; training, validation, and testing datasets. 60% of the data are used for training, 20% for validation, and 20% for testing. Any ANN consists of the following layers, the input layer, hidden layer(s), and the output layer. A determination of the optimum number of hidden layers and the number of neurons in each hidden layer is required to have the best estimation, this is done using the mean square of error (MSE). A supervised ANNs was created for induced fractures formations. A decision was made to have one hidden layer in the network with ten neurons in the hidden layer. Since there are many training algorithms to choose from, it was necessary to choose the best algorithm for this specific data set. Ten different training algorithms were tested, the Levenberg-Marquardt (LM) algorithm was chosen since it gave the lowest MSE and it had the highest R-squared. The final results showed that the supervised ANN has the ability to predict lost circulation with an overall R-squared of 0.925 for induced fractures formations. This is a very good estimation that will help the drilling personnel prepare remedies before entering the losses zone as well as adjusting the key drilling parameters to avoid or at least mitigate losses as a proactive approach. This ANN can be used globally for any induced fractures formations that are suffering from the lost circulation problem to estimate mud losses.
As the demand for energy increases, the drilling process is becoming more challenging. Thus, more advanced tools such as ANNs are required to better tackle these problems. The ANN built in this paper can be adapted to commercial software that predicts lost circulation for any induced fractures formations globally.
The use of high viscosity friction reducers (HVFR) as alternatives to guar-based fluids to improve proppant transport and lessen formation damage has increased rapidly. While several product options are available, the criteria for selection of a product has focused on viscosity at 300 RPM (511s-1) that meets or exceeds that of linear gel fluids. However, there has been limited data available on what the target viscosity should be, how it influences the fluid's ability to transport sand, and the potential for damage to proppant conductivity. This study presents methodology used to screen HVFR's and results on product performance, which identified a need for alternative specifications to viscosity to achieve maximum performance.
The proppant transport capacity in dynamic conditions was evaluated for twenty-eight commercially available friction reducers and HVFR's in field waters which could have up to 40,000 TDS. A slot flow apparatus was used to mimic fluid flow through a fracture under different shear and flow rate conditions. Viscosity and elasticity measurements were also obtained using an advanced rotational rheometer. For comparison, linear gel and crosslinked guar fluid were also evaluated.
While viscosity at 300 RPM (511s-1) and more recently high viscosity at lower shear rates, have been used for selection of HVFR's, these parameters alone do not indicate proppant carrying capacity. The authors did not find a correlation between higher viscosity and better proppant transport, rather they propose that too high a viscosity can negatively impact transport. The results provided insight into the effect of flow rate on proppant transport, with some HVFR's that exhibited higher viscosities at low shear, losing their transport capacity at the same low shear. Elasticity testing of those same products suggested that HVFR's have a critical elasticity range at which they will provide optimal performance. Polymer residuals were also evaluated on proppant post-test and compared to traditional linear gels and crosslinked fluids. Results suggested potential for damage if HVFR's are used without breakers. Different viscosity targets should be set when selecting a HVFR and coupled with other testing criteria such as elasticity and dynamic proppant transport.
This paper provides insight into the need for development of standardized test criteria for HVFR selection. Further testing and screening of HVFR's will help increase the understanding of key factors influencing sand transport and their effect on proppant pack conductivity.
Cement sheath is a critical barrier for maintaining well integrity. Formation of micro-annulus due to volume shrinkage and/or pressure/temperature changes is the major challenge in achieving good hydraulic seal. Expansion of cement after the placement is a promising solution to this problem. Expanding cement can potentially close micro-annulus and further achieve pre-stress condition because of the confinement. Primary aim of this paper is to investigate mechanical integrity of different pre-stressed cement system under loading condition.
To achieve the objectives, finite element modelling approach was employed. Three dimensional computer models consisting of liner, cement sheath, and casing were developed. Pre-stress condition was generated by modelling contact interference at the cement-casing interface. Three cement (ductile, moderately ductile, and brittle) were considered for simulation cases. Wellbore and annulus pressure were applied. Resultant, radial, hoop, and maximum shear stresses were investigated at the cement-pipe interface to assess mechanical integrity. For comparison purpose, similar simulations were conducted using cement sheath without pre-stress and cement system representing uniform volume shrinkage and presence micro-annulus.
For constant wellbore pressure, the radial stresses observed in all three types of cement system were practically similar and decreased as pre-stress was increased. Hoop stress also reduced with increase in compressive pre-load. However, their absolute values were distinct for different cement types. These results indicate that cement system with compressive pre-load can notably reduce the risk of radial crack failure by providing compensatory compressive stress. However, on the contrary, the maximum shear stress developed at cement-pipe interface, increased because of pre-load. This can compromise the mechanical integrity by reducing the safety margin on shear failure. Thus, the selection of expansive cement should be made after carefully weighing reduced risk of radial failure/debonding against the increased risks of shear failure.
This paper provides novel information on expanding cement from the perspective of mechanical stresses and integrity. Modelling approach discussed in this work, can be used to estimate amount of pre-stress required for a selected cement system under anticipated wellbore loads.
Computer vision (CV) techniques were applied to X-ray computed tomographic (CT) images of reservoir cores to evaluate their potential for rapidly identifying fractures and other lithologic/geologic characteristics. The analyses utilized feature-labeled CT cross sectional images, themselves distributed submillimeter voxels of density- and atomic number-sensitive CT Numbers, as inputs to a Fully Convolutional Neural Network (FCN) for semantic segmentation of reservoir core features. In FCN, an image is interrogated using a series of sliding windows at various scales to create weighted filters to reduce error between classes in training images. These networks of filter layers were used to assign probabilities of classes, which were upscaled back to the original image dimensions resulting in probabilistic class assignments onto each pixel. FCN model accuracy, defined by its ability to replicate manually-assigned labels in the raw (unannotated) training image stack, was at least 80% and generally improved with the size of the training set. Once the labels were assigned, the underlying feature frequency, orientation, and size were measured in 3D volume reconstructions using algorithms modified from standard image analysis software. This method allowed users to endow a classification model with subject matter knowledge for further, autonomous label prediction. Thus, while initial image annotation was labor intensive, subsequent images were rapidly classified once the model was built. The classified labels were analyzed for abundance, orientation, and size of fractures were calculated to characterize spatial information of these features. FCN combined with fracture labeling improved knowledge capture and automation of fracture identification. Models trained by high quality 3D datasets can greatly reduce the time needed to describe subsequent core. The method demonstrated is not limited to fractures, other lithologic/geologic features could be trained using the same method, which may result in additional efficiencies.
Understanding the behavior of water-in-crude-oil emulsions is necessary to determine its effect on oil and gas production. The presence of emulsions in any part of the production system could cause many problems such as large pressure drop in pipelines due to its high viscosity. Electrical submersible pumps (ESPs) and gas lift are commonly used separately in lifting crude oil from wells. However, the use of downhole equipment and instruments such as ESPs that cause mixing can result in the formation of an emulsion with a high viscosity. The pressure required to lift emulsions is greater than the pressure required to lift non-emulsified liquids. Lifting an emulsion decreases the pressure drawdown capabilities, lowers production rate, increases the load on the equipment, shortens its life expectancy and can result in permanent equipment damage. Methods and apparatus which reduce the load on the pump, therefore, are desirable. The present paper is directed to understand the behavior of water-in-oil emulsions in artificial lift systems, mainly through gas lift.
Two stable water-in-oil synthetic emulsions were created in the laboratory and their rheology and stability characteristics were measured. One contained crude oil and the other, mineral oil. The second stage included measuring the effect of gas lift exposure on the emulsion behavior and characteristics. The results of the present work indicate that water-in-oil emulsions can be destabilized, and their viscosities lowered under gas exposure. The effect of gas injection on the emulsion was linked to the initial conditions of the emulsion as well as the gas type, injection rate and exposure time.
The present study is directed to methods and systems for combining both ESPs and gas lift for the purpose of improving and simplifying the lift of water-in-oil emulsions from oil wells. The novel methods and apparatus are based on the discovery that by adding gas above the ESPs in the wellbore, the viscosity of an oil-in-water emulsion is actually reduced, thus making it easier to lift oil from the well and extending the life of the ESP. Therefore, in addition to the normal benefits of gas in aiding the lift of liquids, if the gas lift valve is installed at a calculated distance above the pump location, the emulsion viscosity can be reduced. This reduces the load on the ESP.
The primary purpose of using traditional friction reducers in stimulation treatments is to overcome the tubular drag while pumping at high flow rates. Hydraulic fracturing is the main technology used to produce hydrocarbon from extremely low permeability rock. Even though slickwater (water fracturing with few chemical additives) used to be one of the most common fracturing fluids, several concerns are still associated with its use, including usage of freshwater, high-cost operation, and environmental issues. Therefore, current practice in hydraulic fracturing is to use alternative fluid systems that are cost effective and have less environmental impact, such as fluids which utilize high viscosity friction reducers (HVFRs), which typically are high molecular weight polyacrylamides. This paper carefully reviews and summarizes over 40 published papers, including experimental work, field case studies, and simulation work. This work summarizes the most recent improvements of using HVFR’s, including capability of carrying proppant, reducing water and chemical requirements, its compatibility with produced water, and environmental benefits in hydraulic fracturing treatments. A further goal is to gain insight into the effective design of HVFR based fluid systems.
The findings of this study are analyzed from over 26 field case studies of many unconventional reservoirs. In comparing to the traditional hydraulic fracture fluids system, the paper summaries many potential advantages offered by HVFR fluids, including: superior proppant transport capability, almost 100% retained conductivity, cost reduction, minimizing chemicals usage by 50%, less operating equipment on location, reducing water consumption by 30%, and fewer environmental concerns. The study also reported that the common HVFR concentration used was 4gpt. HVFRs were used in the field at temperature ranges from 120°F to 340°F. Finally, this work addresses up-to-date challenges and emphasizes necessities for using high viscosity friction reducers as alternative fracture fluids.