The artificial lift system (AL) is the most efficient production technique in optimizing production from unconventional horizontal oil and gas wells. Nonetheless, due to declining reservoir pressure during the production life of a well, artificial lifting of oil and gas remains a critical issue. Notwithstanding the attempt by several studies in the past few decades to understand and develop cutting-edge technologies to optimize the application of artificial lift in tight formations, there remains differing assessments of the best approach, AL type, optimum time and conditions to install artificial lift during the life of a well. This report presents a comprehensive review of artificial lift systems application with specific focus on tight oil and gas formations across the world. The review focuses on thirty-three (33) successful and unsuccessful fieldtests in unconventional horizontal wells over the past few decades. The purpose is to apprise the industry and academic researchers on the various AL optimization approaches that have been used and suggest AL optimization areas where new technologies can be developed.
The Marcellus formation has begun to attract more attention from the oil and gas industry. Despite being the largest shale formation and biggest source of natural gas in the United States, it has been the subject of little research. To fill this gap, this study experimentally examined the rock properties of twenty core samples from the formation.
Five tests were performed on the core samples: X-ray computerized tomography (CT) scan, porosity, permeability, ultrasonic velocity, and X-ray diffraction (XRD). CT-scans were performed to identify the presence of any existing fracture(s). Additionally, helium was injected into the core samples at four different pressures (100 psi, 200 psi, 300 psi, and 400 psi) to determine the optimal pressure for porosity measurements. Complex Transient Method was employed to measure the permeabilities of the core samples. Ultrasonic velocity tests were conducted to calculate the dynamic Young's moduli (E) and the Poisson's ratios (ν) of the core samples at various confining pressures (in increments of 750 psi between 750 psi and 4,240 psi). Finally, the mineralogical compositions of the core samples were determined using the XRD test.
The results of the CT-scan experiments revealed that seven core samples contained fractures. The porosity tests yielded an optimal pressure of 200 psi for porosity measurement. The measured porosities of the samples were between 6.43% and 13.85%. The permeabilities of the samples were between 5 nD and 153 nD. The results of the ultrasonic velocity tests revealed that at the confining pressure of 750 psi, the compressional velocity (Vp) ranged from 18,411 ft/s to 19,128 ft/s and the average shear velocities (Vs1 and Vs2) ranged from 10,413 ft/s to 11,034 ft/s. At the same confining pressure, the Young's modulus and Poisson's ratio ranged from 9.8 to 10.8 million psi and 0.25 to 0.28, respectively. Increase in the confining pressure resulted in increases in the Vp, Vs, Young's moduli, and Poisson's ratios of the samples. The results of the XRD test revealed that the samples were composed of calcite, quartz, and dolomite.
This study is one of the first to characterize core samples obtained from the formation outcrop by performing five tests: CT-scan, porosity, permeability, ultrasonic velocity, and XRD. The results provide detailed insights to researchers working on the formation rock properties.
In shale formations, operators are constantly seeking new technologies to improve proppant transport and conductivity in order to boost production. A novel technique known as surface modified proppant (SMP) has been pumped in more than a dozen wells in the United States, with proven results of increased production. This paper demonstrates and analyzes a case study for a Marcellus shale development where two wells are presented. Well A applied the SMP technique while the offset, Well B, was stimulated without the technology. After three years, Well A yielded an 18% increase in normalized cumulative gas production over the offset Well B.
In presenting the benefits of this technique, the paper provides a brief overview of the development of the conductivity enhancer; the case study; 3D reservoir and hydraulic fracturing simulator selection; model setup and simulation results. SMP is a chemical additive that, when pumped, creates a buoyancy effect of proppant particles upon entering the fracture network. This dynamic SMP application also propels proppant transportation, prevents proppant settling and enhances the fracture network conductivity by increasing the volume by which sand inhabits the fracture network. Increasing the proppant pack height enables deeper penetration into the fracture network, allowing for an increase in proppant distribution and ultimately enhancing the stimulated rock volume (SRV). We have been able to prove the application in both the lab and field scale tests. The impact of the SMP proppant is investigated by performing numerical simulations of hydraulic fracturing and subsequent production.
Along with clear results showing better proppant placement using the simulator with the conducted study, we further explain the completion effectiveness. We outline advantages and the ease of pumping the SMP, including design optimization, thus making this technology cost beneficial.
Hydraulic fracturing is a typical and vital technique applied in shale gas reservoir development. Numerical simulation used to be a common tool to optimize the parameters in hydraulic fracturing design determining the stage numbers, injection pressure, proppant amount, etc. However, the current understanding of shale gas storage and transport mechanism (e.g. adsorption/desorption, diffusion) is basically adopted from the lessons learned from coal seams through past experience, which might not help an efficient numerical simulation development.
In this study, how artificial intelligence assisted data driven models assist the hydraulic fracturing design in shale gas reservoir is discussed. It starts by collecting field data and generate a spatial-temporal database including reservoir characteristics, operational/production information, completion/stimulation data and other variables, Neural Network models are then developed to study the impacts of all parameters on gas production as well as perform history matching of the field history. The AI assisted model with acceptable matching of field data can be used to model different hydraulic fracturing design scenarios and provide predictions on well production.
Molecular diffusion plays an important role in oil and gas migration and transport in tight shale formations. However, there are insufficient reference data in the literature to specify the diffusion coefficients within a porous media. This study aims at calculating diffusion coefficients of shale gas, shale condensate, and shale oil at reservoir conditions with CO2 injection for EOR/EGR. The large nano-confinement effects including large gas-oil capillary pressure and critical property shifts on diffusion coefficient are examined. An effective diffusion coefficient that describes the diffusion behavior in a tight porous solid is estimated by using tortuosity-porosity relations as well as the measured shale tortuosity from 3D imaging techniques. The results indicated that nano-confinement could affect the diffusion behavior through altering the phase properties, such as phase compositions and densities. Compared to bulk phase diffusivity, the effective diffusion coefficient in a porous shale rock is reduce by 102 to 104 times as porosity decreases from 0.1 to 0.03.
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.
North American market with growing trend of unconventional shale gas reservoirs has warranted rapid development in hydraulic fracturing technology. The long horizontal wells are completed using multi zone plug and perf method that requires multiple zones to be fracked optimally to minimize nonproductive time (NPT). Frac plugs plays vital role in hydraulic fracturing in isolating the multiple zones of the wellbore for operations up to 10,000 psi pressure and 250°F temperature. In this paper advanced computational analysis is conducted to optimize the composite frac plug design for successful operations. Comprehensive laboratory testing is conducted, and digital solutions are compared against the test data to validate the new composite frac plug design. The traditional frac plug design requires effort in milling out the plug and further flushing out the cuttings that adds to the operational time. An alternative is to utilize composite plug that allows ease in milling and reduction in cuttings than traditional design. Numerical analysis is conducted to evaluate the feasibility of composite frac plug design utilizing three-dimensional finite element analysis (FEA) simulations to predict the slip holding capacity. Extensive laboratory testing is conducted for the composite frac plug to validate the digital analysis results. FEA simulations are performed for different configurations of frac plug design by varying number of slip buttons and composite material for slips. FEA results underscored best possible slip button configuration that can successfully work at desired pressure and temperature. Laboratory testing corroborated with digital analysis results and indicated as efficient design that reduced NPT and ensured successful hydraulic fracturing operations. This work assisted in optimizing design quickly and reduced time and cost associated with laboratory testing. This work elucidates use of digital solutions along with laboratory testing for design optimization of composite frac plug. This frac plug has been successfully utilized for several jobs in Marcellus shale play.
Underbalanced drilling via air drilling is deeply rooted in the Northeast United States due to its distinct geology, high rates of penetration (ROP) and drilling efficiency, and low cost of circulating material. The active drilling programs of several independent operators in the Marcellus and Utica Basins are well suited for air drilling down to the final kick off point by virtue of competent, stable formations, low static reservoir pressures, and manageable water ingress to the wells. Air drilling provides near-atmospheric pressure at the borehole bottom, since there is no fluid column with resulting hydrostatic pressure. The result is very high ROP with essentially 100% drilling efficiency, allowing the completion of intervals in one or two bit runs. A service company deployed a cross-functional product development team to optimize oilfield air bits for these applications over the last two years, resulting in decreased drilling costs through increased performance and reliability.
The oilfield air drilling environment places unique challenges on drill bit design due to the increased risk of downhole vibrations, corrosion, abrasive wear, heat generation, and seal infiltration of very fine cuttings. The application requirements have increased due to deeper intervals requiring passage through multiple high unconfined compressive strength formations, extended tangent angles, and rising input energy levels. Accordingly, enhancements to both the cutting structures and sealed bearing systems were vigorously pursued. Several cutting structure design iterations were evaluated in both laboratory and field tests. A new sealed bearing system was developed and implemented for increased life and reliability. Modifications to the bit body for stability were included, and the bit hydraulics were further optimized.
Through an understanding of the objectives and application challenges, unique solutions were developed for Northeast oilfield air drilling applications. The optimization process for the new air bit designs is described, and the resulting positive performance metrics are presented. Improvements were observed in distance drilled, ROP, seal effective rate, and dull condition. Lessons learned were also used to refine the recommended drilling parameters and practices through the challenging formations encountered in these tangent sections, which can span in excess of 7000 feet. These enhancements all contributed to reduced drilling cost and days per well, for increased rig productivity.
The natural gas fields throughout the Marcellus and Utica Basins in the Northeast U.S. continue to deliver rising total gas production for the U.S. and the world through increased capacities in pipelines and LNG trains. Improved drilling performance as documented in this paper are driving continuous improvement in the overall upstream drilling economics of the region.
Friction reducer (FR) performance has been enhanced by adding a FR booster in both fresh water and up to 100% high total dissolved solids (TDS) produced water during hydraulic fracturing applications. However, it is not well understood how the boosters actually increase FR performance during pumping and the effects they have on surface treating pressure and proppant transport. Both laboratory results and field studies of FR and boosters are discussed. Additionally, it was observed that tailored booster chemistry appears to increase FR viscosity significantly, thereby helping ensure better proppant transport during fracturing. Flow loop and viscosity tests were conducted to demonstrate the benefits of using a booster and the results were analyzed to understand the potential mechanisms that dictate the observed phenomena. Laboratory results suggest that the FR booster enables rapid hydration and inversion of FRs, which typically results in decreased treating pressure to approximately 800 psi compared to FRs without boosters. This pressure decrease during pumping for a single fracture stage has been frequently observed in several shale plays, such as the Wolfcamp, the STACK/SCOOP, and the Marcellus/Utica. A lower FR concentration can be used to transport proppant because the booster helps reach the same or higher viscosity. Case studies are discussed to further understand the synergy between FRs and boosters.
One of the biggest challenges in unconventional reservoirs has been the accurate prediction of the production performance of wells before turning them in line. Typically, analogous type curves are generated based on each area of interest (AOI). Within each area of interest, numerous variations can be found in completions design, well spacing, geologic/geochemical/geomechanical properties. Therefore, it is important to take all these variations into consideration for accurate production forecasting as opposed to using an analogous type curve for each area of interest. Analogous type curves are easy to create and have their own merits when performing overview analysis. However, they have limitations when it comes to truly understanding the impact of geologic variability and completions/well spacing design. In addition, it is extremely valuable to predict the production performance of a well in advance considering all variable changes. Operators across various basins have changed multiple completions parameters at a time. It is extremely difficult to obtain the quantitative impact of each parameter on production performance without preconceived bias. Due to variations in production performance of unconventional wells with similar designs, even a direct comparison between adjacent wells can be difficult to interpret. This begs for a non-linear multi-output supervised machine learning (ML) model to predict cumulative (CUM) production per foot over time. In addition, once an accurate model with CUM production per foot is obtained, economic analysis can be performed to interpret the qualitative and quantitative impact of each parameter. While calibrated numerical simulations are powerful tools when predicting production behavior in advance, the biggest limiting factor is the time it takes to calibrate a model and apply various sensitivity analyses. On the other hand, once a trained ML model is developed, running thousands of sensitivities can take seconds.
This paper will describe a dynamic workflow that was used to generate a multi-output supervised ML model which used artificial neural network (ANN) to predict CUM/ft over the first two years. After predicting CUM/ft over the first two years, a production decline curve analysis (DCA) can be fitted through the predicted CUM/ft data to obtain the remaining production performance of the well's life (48 years). Next, economic analysis can be used to run various sensitivities and find the optimum completions design considering commodity pricing, CAPEX, etc. In addition, a supervised random forest (RF) model was used to feature rank the input parameter importance and was compared to the ANN model. The biggest limitation when using such models is extrapolation. These models are used internally for interpolation within the data constraint limits and numerical simulations are used for extrapolation. The development of such a model enables the simultaneous alteration of multiple variables and the prediction of the production outcome over the next two years. Thus, an optimal design can be selected depending on the economic evaluation of each area of interest.