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.
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.
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.
Flow pattern of a multi-phase flow refers to the spatial distribution of the phase along transport conduit when liquid and gas flow simultaneously. The determination of flow patterns is a fundamental problem in two-phase flow analysis, and an accurate model for gas-liquid flow pattern prediction is critical for any multiphase flow characterization as the model is used in many applications in petroleum engineering. The objective of this study is to present a new model based on machine learning techniques and more than 8000 laboratory multi-phase flow tests.
The flow pattern is affected by fluid properties, in-situ flow rates of liquid and gas, and flow conduit geometry and mechanical properties. Laboratory data since 1950s have been collected and more than 8000 data points had been obtained. However, the actual flow conditions are significantly different with any laboratory settings. Therefore, several dimensionless variables are derived to characterize these data points first. Then machine learning techniques were applied on these dimensionless variables to develop the flow pattern prediction models. Applying hydraulic fundamentals and dimensional analysis, we developed dimensionless numbers to reduce number of freedom dimensions. These dimensionless variables are easy to use for upscaling and have physical meanings. We converted the collected data from actual laboratory measurement to the variations of these dimensionless variables. Machine learning techniques on the dimensionless variable significantly improved their predictive accuracy. Currently the best matching on these laboratory data was about 80% using the most recently developed semi-analytical models. Using machine learning techniques, we improved the matching quality to more than 90% on the experimental data.
This paper applies machine learning techniques on flow pattern prediction, which has tremendous practical usages and scientific merits. The developed model is better than current existing semi-analytical or classical correlations in matching the laboratory database.
The supersonic separation is a new approach to dehydrate the natural gas in recent years. In the conventional structure, the straight tube is typically combined with a cyclone to create a strong vortex flow. The shock wave usually occurs near the swirling device in the supersonic separator, which can make the flow unstable and decrease the separation efficiency. Due to removing the negative effects of the shockwave, a newtype helical guide blade is designed as the swirling device, installed in the separate straight tube in the supersonic cyclone separator. The flow characteristics in the supersonic separator was investigated and the geometry structure was optimized by performing the computational fluid dynamics modeling methods. The optimization results showed that the model with a converging tube of 190 mm length, a diverging tube of half-cone angle of 5 and a single blade installed in the middle position, is the best supersonic separator model in the dehydration process, which can create the most stable flow field and achieve the optimum separation. In addition, when the outlet back pressure in the diffuser tube is 1 Mpa 1.5 Mpa, the separation performance will be better.
Cores can be considered the ground truth only if we eliminate or minimize their damage during core cutting, tripping, and surface handling. Such damage would adversely alter their properties. An important source of core damage is during tripping, when quick decompression might cause damage because of the induced microfractures. In this paper, a state-of-the-art geomechanical model is introduced and applied for determining the safe-tripping rates.
The thermo-poroelastic (T-P-E) geomechanical approach used in this study includes the mathematical derivation of the diffusion time required for the imposed pore-pressure difference to dissipate while also considering the effects caused by the temperature changes, mudcake, and swabbing. The work uses different approaches for fluid modeling in a transient manner during tripping for the water-bearing, gas-bearing, and oil-bearing cores.
In this work, the hydraulic diffusivity and the fluid type have been introduced as the main factors controlling the maximum allowable safe-tripping rates. A relationship between the allowable decompression rate and the hydraulic diffusivity will be presented for each specified fluid type. In addition, the results indicate that water-bearing cores can be safely tripped as quickly as the normal tripping speed of the wireline, even with a core that has a permeability as low as 0.01 md. For gas- and oil-bearing cores, the safe-tripping rates are determined to be much less than the water-bearing cores because the fluids expand with the pressure drop along the journey to the surface. The results show that the tripping rate is the lowest for the oil-bearing cores, particularly in the vicinity of the bubblepoint and gas critical pressure (because the gas expansion pushes the oil and applies significant viscous forces across the core pore throats).
This paper is a novel work developing T-P-E and mathematical models for the case of core tripping considering the effects of pore-pressure change, temperature change, mudcake, and swabbing. The hydraulic diffusivity and the fluid type have been considered as the controlling factors. The approach has been applied for modeling the tripping of water-, gas-, and oil-bearing cores to provide maximum allowable tripping rates.
The main purposes of employing cement in oil wells are to isolate the zones within formations, secure casing from axial loading and corrosion and improve wellbore integrity. There are plenty of nanomaterials represented in the literature which were introduced to cement in order to advance the strength and rheological properties of cement slurry. The objective of this study is to propose a novel nanomaterial which can upgrade the mechanical and rheological properties of cement. The smaller the size of Nano-particles, the higher surface area and hence higher efficiency they possess to advance particular properties of the support material. Bio-templating has been offered as an approach to reduce the size of utilized nanoparticles. In this study, Nanosilica particles were synthesized and functionalized using modified sol-gel method. Bio-templating was then implemented through crosslinking of the procured Nanosilica with soluble egg protein using glutaraldehyde. In order to investigate the effect of bio-templated Nanosilica on cement slurry, synthesized Nanosilica was added to cement and rheological and mechanical experiments were conducted. To validate the performed bio-templating, ATR-FTIR spectrum was acquired which confirmed successful crosslinking between the functionalized Nanosilica and SEP. Furthermore, experimental tests were conducted to evaluate the effect of bio-templated Nanosilica on mechanical and rheological properties of neat cement. The results were then compared to inclusion of commercial Nanosilica in cement. Through the rheological studies, it was found that the modified Nanosilica has acted as dispersant in cementitious system by decreasing the plastic viscosity of cement and maintaining the density. It was also obtained that novel bio-templated Nanosilica has significantly increased uniaxial compressive strength of cementitious system by 16.59% upon addition of only 0.25 wt.%. It was due to its pozzolanic reaction in cement and its pore filling effect where the porosity of cementitious system was decreased. The proposed synthesized Nanosilica demonstrates superior results than commercial Nanosilica which shows its remarkable efficiency in cement strength reinforcement and rheological properties improvement. The research study has successfully proposed a novel method to utilize biomaterial waste in the process of synthesizing Nanosilica particles which is not only environmental friendly but also yields in phenomenal rheological and mechanical properties of Class G cement.
Han, Guoqing (China University of Petroleum) | Ma, Gaoqiang (China University of Petroleum) | Ling, Kegang (University of North Dakota) | Gao, Yue (Sinopec Research Institute of Safety Engineering) | Zhang, HE
Nowadays, unloading gas wells with coiled tubing is a common application to the field. However, there is still lack of adequate understanding of dynamic behavior of the unloading process. Especially, there is no mature dynamic simulator for this unloading process in China. Therefore, it is necessary to study the dynamic process of liquid unloading with coiled tubing for parameter analysis and optimization. This paper studies dynamic process of liquid unloading by gas lift with coiled tubing. This unloading process includes three stages: liquid rising in tubing, liquid slug production, and liquid production by entrainment. In each stage, the mass and linear momentum conversation equations are applied to each component of the system. The components of each stage includes coiled tubing, coiled tubing-tubing annulus, liquid slug, gas bubble, and liquid film. And empirical correlations used in model include surface gas injection choke, check valve, friction factor, the relationship between the gas bubble and the liquid slug velocity, inflow performance relationship, and fluid properties. From the above, the dynamic model couples real-time change of inflow performance relationship with tubing performance. The LU factorization and the Euler method are used to derive the dynamic model, and program the dynamic model with the Visual Basic language to calculate and analyze all the variables describing a whole dynamic process as functions of time. Among all these variables, the most important ones include gas injection rates, pressures at various locations, positions of the liquid slug and gas bubble, and various velocities. Based on the dynamic model, the dynamic simulation of liquid unloading process is achieved, and the basis for design optimization of parameters is provided.
Sucker rod pumps provide mechanical energy to lift oil from bottom hole to surface when oil wells do not have enough energy to produce the oil through natural flow. It is efficient, simple, easy to be operated, and can be applied to slim holes, multiple completions, and high-temperature and viscous oils. The disadvantages include excessive friction in crooked holes, solid-sensitive problems, low efficiency in gassy wells, limited depth, and bulky volume. The load on the rod is one of the key factors that dictate the maintenance frequency of pumping unit, energy consumed to lift the fluid, and the optimization of pumping system operating parameters.
The cyclic load applied on the rod causes the fatigue and finally the failure of the rod if not designed properly. The rod load is a function of friction force, plunger acceleration/deceleration, weights of plunger, fluid being lifted, and sucker rods string, and the pressures above and below on plunger. Literature review indicates that a model to accurately calculate the load of a pumping cycle is highly desired. In this study, we couple the wellbore with reservoir performance to better analyze the dynamics of pump system, which yields more accurate results.
In this study, force balance during the pumping cycle is analyzed. Friction force due to the movement of the plunger and the rod, buoyant force, and gravity force are included in the modeling. The effects of acceleration and deceleration of the plunger on rod are considered. The sensitivity of pumping speed is investigated. This study proposed a more general model comparing with former researches because more factors that affect the load applying on rod are included. Including the friction force due to the viscous fluid is critical to rod load analysis in pumping heavy oil.
The proposed model is significant to the cyclic fatigue and failure analysis of rod in sucker rod pumping system. It can be used to predict the possible failure point for rod string by analyzing load along the whole string. It is also a useful tool to design the tapered rod string to minimize the maximum rod load while achieving optimum rod string life. Therefore, an optimization of sucker rod pumping system is implemented by balancing the tradeoff between the maximum rod string life (or rod size) and the minimum rod load (or lowest energy consumption).
Seright, Randall S. (New Mexico Institute of Mining and Technology) | Wang, Dongmei (University of North Dakota) | Lerner, Nolan (Cona Resources Limited) | Nguyen, Ahn (Cona Resources Limited) | Sabid, Jason (Cona Resources Limited) | Tochor, Ron (Cona Resources Limited)
This paper examines oil displacement as a function of polymer-solution viscosity during laboratory studies in support of a polymer flood in Canada’s Cactus Lake Reservoir. When displacing 1,610-cp crude oil from field cores (at 27°C and 1 ft/D), oil-recovery efficiency increased with polymer-solution viscosity up to 25 cp (7.3 seconds-1). No significant benefit was noted from injecting polymer solutions more viscous than 25 cp. Much of this paper explores why this result occurred. Floods in field cores examined relative permeability for different saturation histories, including native state, cleaned/water-saturated first, and cleaned/oil-saturated first. In addition to the field cores and crude oil, studies were performed using hydrophobic (oil-wet) polyethylene cores and refined oils with viscosities ranging from 2.9 to 1,000 cp. In field cores, relative permeability to water (krw) remained low, less than 0.03 for most corefloods. After extended polymer flooding to water saturations up to 0.865, krw values were less than 0.04 for six of seven corefloods. Relative permeability to oil remained reasonably high (greater than 0.05) for most of the flooding process. These observations help explain why 25-cp polymer solutions were effective in recovering 1,610-cp oil. The low relative permeability to water allowed a 25-cp polymer solution to provide a nearly favorable mobility ratio. At a given water saturation, krw values for 1,000-cp crude oil were approximately 10 times lower than for 1,000-cp refined oil. In contrast to results found for the Daqing polymer flood (Wang et al. 2000, 2011), no evidence was found in our application that high-molecular-weight (MW) hydrolyzed polyacrylamide (HPAM) solutions mobilized trapped residual oil. The results are discussed in light of ideas expressed in recent publications. The relevance of the results to field applications is also examined. Although 25-cp polymer solutions were effective in displacing oil during our corefloods, the choice of polymer viscosity for a field application must consider reservoir heterogeneity and the risk of channeling in a reservoir.