bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital Solutions to Optimize Jet Pump Technology for Production Enhancement
Authors: Deshpande Kedar , Knoeller Michael , Patkar Vivek
Published: April 2019

Artificial lift systems provide a reliable means for ensuring production through depleted wells. Traditional artificial lift technology is seriously challenged and has shown faster wear in tough operating environments at greater depths, high dog leg severities and multi-phase fluid environment. Jet pump technology with no moving parts and compact design is an excellent alternative for production enhancement in most challenging downhole conditions. In this paper digital computational fluid flow analysis is conducted to optimize the jet pump design to improve operational life of the jet pump and reduce non-productive time (NPT). Comprehensive laboratory testing is conducted and digital solutions are compared against the test data to validate the new jet pump technology.

The operation of jet pump starts with flow of high pressure power fluid from surface into wellbore that travels through jet pump nozzle causing reduction in pressure which in turn draws in the reservoir fluid into jet pump throat. The low pressure generated at throat due to venturi effect can cause cavitation in certain scenarios and leads to reduced operational life of jet pump. To address this issue an alternative inverse jet pump is proposed that reverses the flow path of power fluid and production fluid. Numerical analysis is conducted to evaluate the feasibility of inverse jet pump design. Three-dimensional computational fluid dynamics (CFD) simulations are conducted using coupled algorithm with Reynolds-Averaged Navier-stokes (RANS) equation and k-ε turbulence model to predict the pressure and velocity flow field. Extensive laboratory testing is conducted in flow loop for the inverse jet pump design to validate the digital analysis results.

CFD simulations are performed for different configurations of inverse jet pump by varying throat diameter and length of mixing chamber for operating production and power fluid flow rates. CFD results underscored the pressure and velocity profiles along the flow paths and based on digital analysis using CFD it is observed that innovative inverse jet pump design reduces probability of cavitation. Laboratory testing corroborated with digital analysis results and indicated improvement in operational life for inverse jet pump technology. Extensive usage of advanced computational modeling in this work assisted in optimizing design quickly and reduced time and cost associated with laboratory testing. This work elucidates use of digital solutions for design optimization of new production technology and underscores simulation-based-design as faster and cost effective method.
Three Weeks Oil Production Shutdown Avoided and Tremendous Cost Savings Achieved With no Downtime During Largescale Replacement of Electrical Equipment
Authors: Schröder Stephan Rainer
Published: April 2019

This paper highlights how flexible and innovative engineering can replace electrical systems in existing and producing offshore facilities achieving minimized losses of production. It shows the opportunities realizing a major electrical infrastructure project on an offshore platform within a short timeframe and limited human resources. The fact that intelligent and simple solutions connecting a new offshore module into the existing infrastructure cut down the expected three weeks of production downtime to only four hours for each individual Electrical Submersible Pump System (ESP system). The main aim of this project was to avoid any shutdown of the production due to long installation phase for new equipment and decommissioning phase for the existing equipment. The whole project was split into well sized work-packages and interfaces to the existing infrastructure were considered.

Given the restricted space at Mittelplate, a new compact modular containerized solution was found allowing to set up offshore switchgear containers prior to removal of existing and operating ESP system. To avoid negative consequences during offshore installation and commissioning, tests of the entire simulation packages were completely run onshore. Based on lessons learned and training effects gained, several teams were able to reconnect 16 ESP without any downtime. Specially designed adapters allowed to directly connect the new Variable Speed Drive (VSD) to the existing Distributed Control System (DCS) without any production downtime. In parallel to onshore component tests, the project team started preparatory work on Mittelplate platform. One team focused on the installation of adapters, the second team was responsible for adaptation of the process graphics to the DCS. At the same time, the third team was busy installing and connecting the new power cables between variable speed drive system and step up transformer. After notice of completion given by all teams, system tests and commissioning were carried out together with the operator well by well.

Due to parallel work of three teams the wells could be successfully reconnected within unprecedented four hours average each. Furthermore, the whole work was carried out without any Lost Time Incident (LTI).
Recovery Mechanisms for Nano-Confined Oil in Source Rocks using Lean Gas Injection
Authors: Baek Seunghwan , Akkutlu I. Yucel
Published: April 2019

Organic matter in source rocks stores oil in significantly larger volume than that based on its pore volume due to so-called nanopore confinement effects. However, during production and depletion, recovery of that oil is low. In this paper, we introduce the nano-confinement effects and explain their impact on the release of oil molecules. We propose to control these effects and increase the oil recovery using lean gas injection, such as ethane or carbon-dioxide. We identify and discuss microscopic-level oil recovery mechanisms that appear during the soaking and production stages.

Due to the nature of the problem, molecular Monte Carlo simulation method is used for the investigation. A multi-component hydrocarbon mixture is considered in model organic pores under reservoir conditions. The fluids stored in pores are in thermodynamic equilibrium with a nearby bulk fluid in a fracture. The fluid composition in pores varies with the size of the pore and becomes progressively heavier during the production as the bulk fluid pressure is reduced. The lean gas molecules are introduced to the nanopores by adjusting the bulk fluid composition and pressure to the desired values. Simulations are used to predict fate of in-situ and the injected molecules when the system is reached to equilibrium.

Results show that oil in smaller nanopores is richer in heavy components compared to the bulk oil outside in the micro-crack. Compared to gas reservoirs, the impacts of the nano-confinement on in-place fluid volume is not significant. Recovery of the confined oil is typically below 15 % indicating that pressure depletion and fluid expansion is no longer an effective recovery mechanism. Ethane injection shows higher recovery performance than CO2 injection; it improves recovery up to 90 %, depending on its composition in the fracture. Ethane recovers 5-20 % higher than carbon dioxide in both large pores and nanopores, because ethane molecules are more effective in vaporizing the heavier molecules in the pore. In addition, ethane reduces viscosity of the confined oil, and its diffusion is faster than CO2. In summary, lean gas injection is effective in recovering the oil but its delivery to the matrix using fractures and micro-cracks under closure stress makes injection operations challenging in the field.
Analytical Investigation of the Confinement Effect on Capillary Condensation Pressure of Fluids in Nanopores
Authors: Yang Gang , Chai Di , Fan Zhaoqi , Li Xiaoli
Published: April 2019

Phase behavior in nanopores, because of its widespread industrial applications, has attracted great attention from numerous researchers in recent years. However, there are still several aspects that are not fully understood in this area, such as the confinement effect on saturation pressure, critical properties, and phase boundary.

In this work, real gas effect is firstly incorporated into the original Kelvin equation, along with the pore size effect on surface tension, the multilayer adsorption, and the molecule-wall interaction potential to improve the accuracy of the capillary condensation pressure calculation. Firstly, the validity of the original Kelvin equation is examined by calculating the capillary condensation pressure of pure fluids at different pore sizes. Subsequently, the compressibility factor is computed with a modified Peng-Robinson equation of state and the molecule-wall interaction potential is correlated with the number of adsorption layers in nanopores, both of which are coupled into the original Kelvin equation. Consequently, the modified Kelvin equation is validated with collected experimental data from the literature.

It is found that the capillary condensation pressure computed by the original Kelvin equation manifest a significant deviation from those measured from experiments at pore size smaller than 15 nm. At pore size of 2 nm, the capillary condesantion pressure calculated with the original Kelvin equation is 627.5% and 407.8% higher than the experimental data for nitrogen and argon, respectively. Among the four factors which are incorporated into the original Kelvin equation for modification, molecule-wall interaction potential has the most significant contribution with a ratio of 72%, while the pore size effect on surface tension has the least to none contribution. The modified Kelvin equation is satisfactory to calculate the suppressed capillary condensation pressure of fluids in nanopores with pore size down to 2 nm. The overall relative devation for 3 data points of nitrogen at 77 K and 5 data points for argon at 87 K is 6.5% and 6.7%, respectively.

This work provides a quantitative understanding of the confinement effect on capillary condensation pressure of fluids, which can help to investigate the phase behavior of reservoir fluids in nano-sized pores more accurately. The newly developed explicitly analytical model can be easily introduced into various simulators to provide a reliable instruction for the development of shale reservoirs.
Evaluation of Hydrophobic Proppant Transport by Aqueous Energized Fluids, Impact of Gas Volume Fraction and Proppant Size: A Holistic Approach
Authors: Pruvot Antoine , McAndrew James , Cisternas Pablo , Quintero Harvey , Wang Chuanzhong , Cherniwchan Denny , O’Neil Bill
Published: April 2019

Hydrophobically coated sand, when combined with gas injection into an appropriate fluid, provides a significant improvement in proppant transport compared to uncoated sand. This supports the expectation that gas bubbles adhering to sand particles improve transport properties. In addition, the increase of nitrogen gas volume fraction within the fracturing fluid significantly enhances proppant suspension, particularly for smaller size proppant. Proppant transport occurs by two mechanisms, suspended transport and bed transport.

This study aims at determining the optimum conditions and composition for a fracturing fluid, comprised of a gas dispersed into an aqueous liquid (but not as a foam), to transport hydrophobically coated proppant. The aqueous phase is comprised of water with a friction reducer, to enhance suspension performance. The impacts of the gas volume fraction of the fluid and of the proppant particle size are studied.

The experimental setup is designed to compare the proppant transport efficiency of different gaseous and/or liquid fracturing fluids. In the present case, high pressure nitrogen (13.8 MPa - 2000 psi) is dispersed within an aqueous fluid. Proppant is then injected at the entrance of a straight pipe section. This central section is equipped with several collectors where the sand can accumulate. After a specific time, the system is shut down and depressurized. Sand collection along the section provides a quantitative measurement of the proppant transport efficiency. Additionally, direct observation through sight glasses allows qualitative assessment of the transport method.

The main impact of increasing the volume fraction of gas is to increase suspended transport, but we also observed a moderate improvement in bed transport. Thus, overall we observed a significant improvement in proppant transport as the gas volume fraction was increased from 10% to 30%. This effect was greatest at the smallest particle size tested, i.e. 40/70 U.S. mesh sand, but was also observed with 30/50 and 20/40 U.S. mesh sands. The upper limit on gas volume fraction was imposed by the nature of the aqueous fluid, which is not designed to operate as a foam. Phase separation effects become dominant at high gas volume fractions. The effect of particle size is attributed to the increasing number of particles present at constant loading by mass.

Here we present data to support the selection of gas volume fraction for use with hydrophobically coated proppant, in order to optimize proppant transport in practical fracturing operations. These data are based directly on proppant transport measurement under high pressure conditions, which enable proper consideration of elasticity and proppant suspension effects of added gas.
A Newly Developed Approach to Evaluate Rock Brittleness and Fracability for Hydraulic Fracturing Optimization in Shale Gas
Authors: Salah Mohamed , Ibrahim Mohamed Mohamed , Ibrahim Mazher , Pieprzica Chester
Published: April 2019

To economically develop the unconventional reservoirs, it is essential to understand the petrophysical and reservoir property variations throughout the entire field in helping to identify sweet spot areas and guide both completion and hydraulic fracturing design.

The brittle shales are more likely to be naturally fractured responding well to hydraulic fracturing. Ductile shales, on the contrary, are more plastic, absorb energy, and are not considered good producers. In such shales, the formation tends to heal any natural or induced fractures. Thus, formation sections with high brittleness are considered good candidates for hydraulic fracturing. However, many researchers argue that this viewpoint is not reasonable, because rock brittleness is not an indicator of rock strength and the current brittleness indices are based on elastic modulus or mineralogy. Brittle rock just has shorter plastic deformation, and it is not certain that it is easier to fracture brittle rock than ductile rock since brittle formation may have greater strength than ductile formation. So, rock fracability term is introduced to correct the shortcoming of rock brittleness. Fracability is defined as the rock failure under the ultimate rock strength in either brittle or ductile formation. The higher the fracability of the formation, the smaller formation strength. Therefore, the good hydraulic fracture candidate is the formation that does not only have high brittleness but also high fracability thus, less energy is required to induce fracture.

A fracability model integrating the rock elastic properties, fracture toughness and confining pressure is presented in this paper. Geomechanical rock properties derived from analysis of full-wave sonic logs and core samples were combined to develop sophisticated models to verify the principle of brittleness and fracability indices and to screen hydraulic fracturing candidate intervals.
Predictive Maintenance for Rod Pumps
Authors: Bangert Patrick , Sharaf Sayed
Published: April 2019

Approximately 20% of all oilwells in the world use a beam pump to raise crude oil to the surface. The proper maintenance of these pumps is thus an important issue in oilfield operations. We wish to know, preferably before the failure, what is wrong with the pump. Maintenance issues on the downhole part of a beam pump can be reliably diagnosed from a plot of the displacement and load on the traveling valve; a diagram known as a dynamometer card. We demonstrate in this paper that this analysis can be fully automated using machine learning techniques that teach themselves to recognize various classes of damage in advance of the failure. We use a dataset of of 35292 sample cards drawn from 299 beam pumps in the Bahrain oilfield. We can detect 11 different damage classes from each other and from the normal class with an accuracy of 99.9%. This high accuracy makes it possible to automatically diagnose beam pumps in real-time and for the maintenance crew to focus on fixing pumps instead of monitoring them, which increases overall oil yield and decreases environmental impact.
Drilling Fluid Impact on Injectivity During Multistage Fracturing in Horizontal Wells
Authors: Asel Sultan , Al Moajil Abdullah , Al-Harbi Bader , Al Darweesh Sajjad
Published: April 2019

Multistage Fracturing (MSF) completions have been extensively used as an economical intervention means to handle extreme downhole environment. To have adequate Injectivity during hydraulic fracturing (HF), sand face permeability should be exposed to minimum formation damage. Impaired injectivity is caused by a mechanical obstruction across wellbore, tight formations (low permeability) and high heterogeneity or invaded particulates by Drill-In-Fluid (DIF) that damaged the formation. Many causes were suspected such as formation heterogeneity, false indication of completion port opening, and damage to the sand face due to drilling filter cake. Solvent treatments, acid wash and tubular slotting are the most reasonable remedies to this issue, adding more cost to the operating company. The objective of this study is to present technical procedures and methodologies followed to investigate impaired injectivity associated with MSF completions. Results and recommendations provide remedial recipes and optimized drilling and production operating procedures. Therefore, realizing a significant cost saving for operating companies.

X-Ray Diffraction (XRD), X-Ray Fluorescence (XRF), and Environmental Scanning Electron Microscope (ESEM) techniques were used to analyze solid samples. HP/HT aging cells were used to conduct solubility testing of filter cake and typical barite/oil-based sludge sample. HP/HT filter press was used to study the effect of time on filter cake build-up at 300°F.

HCl acid showed low solubility for typical oil-based drilling fluid sludge at 310°F. Mutual solvents dissolved the sludge partially at 300°F (e.g. ~40wt% solubility). DTPA and EDTA-based chelating agents showed higher dissolution power compared to the HCl solutions. The addition of mutual solvent to the tested chemicals increased the solubility of the sludge. Among tested chemicals, 90 % DTPA and 5 % mutual solvent provided the higher solubility. High filtration rate was noticed during HP/HT filtration test. The thickness of the filter cake increased significantly as a consequence of filtration/soaking time (e.g., up to a week). Therefore, to avoid filter cake build up and the problems associated with that, the filter cake should be removed immediately after the drilling operations.
Evaluation of Fractured Rocks through Anomalous Diffusion
Authors: Raghavan Rajagopal , Chen Chih-Cheng
Published: April 2019

A minimal mathematical model for transient diffusion in fractured rocks at the well scale with options to link topological and geometrical properties of fractured rocks where the geology is complex is presented. We simulate transient diffusion in systems with complex geology through a transient, interporosity model consisting of three constants to consider both complex structures that may exist at very fine scales and forms that result in long-range connectivity across multiple links in a network. Fractional constitutive flux laws that address super- and subdiffusive influences and result in transient propagation of the form r2~ta, with a≠1, are considered. The spatiotemporal evolution of the transient is documented, and well-codified Flow Regimes and sub-Flow Regimes are cataloged into stages with associated typical characteristics often visible in both short- (buildup) and long-time (flow) well-behaviors. We arrive at interpretations well beyond the ‘linear-flow-regime’ that is the norm. Because the conceptual interpretation is based on a physics-based model, the ideas we present are both scalable and reproducible. We recover classical formulations through a subset of the model considered here. New behaviors, yet to be reported, are discussed.
Artificial Neural Network Modeling of Cyclic Steam Injection Process in Naturally Fractured Reservoirs
Authors: Ersahin Ahmet , Gul Sercan , Ertekin Turgay , Temizel Cenk
Published: April 2019

Introducing heat into a heavy oil reservoir is a well-known enhanced oil recovery (EOR) technique. Cyclic steam injection (CSI), also called as huff and puff, is one of the most common methods used to heat the reservoir to reduce fluid viscosity. Natural fractures provide effective connections throughout the reservoir, which make naturally fractured reservoirs great candidates for steam injection. Numerical simulators are capable of designing CSI operations in dual-porosity systems. However, the use of commercial simulator can be time-consuming when a large number of cases are examined for optimizations. Artificial neural networks (ANNs) work well to solve and classify the non-linear relationships between input and output parameters.

In this paper, one forward and two inverse ANN models are proposed to discuss the performance of CSI in naturally fractured heavy oil reservoirs and to discuss smart proxy models’ mimicking ability of the commonly used numerical models. In this study, we focus on a single injection and soaking cycle for a single well. The first stage of the production starts with initial recovery, and it continues until the oil flow rate drops down to a predetermined threshold value, then, the second stage (the injection phase) takes place. Injection phase is followed by the soaking phase. Delivery of steam creates a heat chamber around the wellbore (stimulated zone) where the reservoir temperature dramatically increases. The non-uniform temperature distribution of the reservoir ends up encountering different viscosity values of the oil.

The forward ANN model successfully forecasts both cumulative oil production profiles and viscosity changes around the wellbore. Reservoir properties, rock and fluid interaction parameters, fluid properties, and injection design parameters (such as steam quality, injection rate, injection time, etc.) were used as input features. A variety of ANN architectures were tested for the minimum testing errors.

The first inverse-looking ANN model, Inverse Model 1, was designed for determining the ideal injection design parameters for a desired cumulative production profile. Once injection design parameters were selected, the forward ANN model was run for those injection design parameters for verification purposes.

Second inverse-looking ANN model, Inverse Model 2, characterizes significant reservoir parameters including; matrix porosity, matrix permeability, fracture permeability, and fracture spacing. It can be laboriously challenging and computationally costly to obtain these parameters for some fields. This ANN model is trained with injection design parameters and resulting performance indicators. All the ANN-based models are controlled by a user-friendly graphical interface for the ease of the user.
Real-Time Steam Allocation Workflow Using Machine Learning for Digital Heavy Oil Reservoirs
Authors: Sibaweihi N. , Patel R. G. , Guevara J. L. , Gates I. D. , Trivedi J. J.
Published: April 2019

Thermal oil recovery processes are widely used to extract bitumen and heavy oil. Traditionally, a predetermined amount of steam is allocated to various injector wells using reservoir model based open-loop optimization. This practice can face a number of constraints including interruptions in well operations and/or surface facilities. Given that steam supply costs are a significant contributor to the overall production cost of heavy oil, dynamic and intelligent allocation of steam to various wells in the oilfield deserves further attention.

In this study, we propose a proactive steam allocation workflow that can learn the effect of steam injection pattern on heavy oil recovery by using machine learning. We employ data analytic predictive models for the short-term forecast of the key performance indicators (KPIs). Model parameters are updated continuously by using a moving horizon approach that considers selected prior data including real-time measurements. An objective function containing predicted KPIs is maximized by manipulating the amount of steam allocated to various injectors in the oilfield. The workflow is repeated on a daily basis for continuous optimum steam allocation.

A case study is performed by using a 3D reservoir model that represents a segment of the steam-assisted gravity drainage (SAGD) operation. For each well, the polynomial model is identified in the time-domain to forecast KPIs. The effectiveness of the proposed method is evident from the results as NPV is increased by almost 25% – 50% compared to the base case with a constant steam injection pattern in all cases studied. Due to the efficient use of available steam, the steam-to-oil ratio is reduced significantly. An adaptive and flexible steam supply is also honored by the proposed workflow, ensuring maximum efficiency of the oil recovery process. Practical implications of the proposed intelligent steam allocation workflow will be consequential in improving the operational efficiency of the digital heavy oil assets, thereby increasing profits and reducing the carbon footprint.
In-Situ Combustion Frontal Stability Analysis
Authors: Zhu Zhouyuan , Liu Yanni , Liu Canhua , Wang Yuhao , Kovscek Anthony Robert
Published: April 2019

Due to the complex chemical reactions and multi-phase flow physics, the displacement front stability for in-situ combustion (ISC) oil recovery processes is not well understood. In this work, we present the theory and numerical simulation for establishing analytical front stability criteria for ISC processes.

We first analyze the four influencing factors for thermal displacement stability: viscous force, heat conduction, matrix permeability changes, and gravity. A thorough analysis of the different zones and displacement fronts in a typical ISC process is conducted, with the most unstable front identified. Second, we establish the analytical solutions for judging the frontal stability. Third, numerical reservoir simulation is performed to study the frontal stability/instability and also to validate the analytical theory. We have carefully selected differential schemes, spatial and temporal discretization to ensure the accuracy of these simulations.

We have identified four major zones and three displacement fronts (reaction zone, leading edge of steam plateau, and oil bank leading edge) in a typical 1D ISC process. The most unstable front with the largest pressure gradient contrast is the leading edge of steam plateau. By establishing material and energy balance and solving the wavy perturbation of the steam front, we obtain the analytical equation for deciding the ISC flood frontal stability. In numerical simulations, we are able to obtain results with enough accuracy to capture unstable ISC displacements and show fingering behavior in different conditions. We have found matrix permeability reduction due to coke deposition has minimal impact on frontal stability. The simulation results are successfully validated with the analytical work for conditions where the ISC process is stable or unstable, which demonstrates its predictive capability for frontal stability.

In conclusion, we have established a theoretical framework to analyze at certain conditions whether the displacement of an ISC process is stable or not. Numerical simulations confirm its predictive capability. It serves as a new reservoir engineering tool for the implementation and design of practical ISC projects.
Improvement of Reservoir Management Efficiency Using Stochastic Capacitance Resistance Model
Authors: Kim Tae Hyung
Published: April 2019

Lost Hills is a dual permeability Diatomite reservoir that is distinct from conventional reservoirs. Application of numerical simulation has been limited throughout field life due to the complex nature of the diatomite including low permeability (∼ 1 md) but high porosity (∼ 50%) and weak rock strength (∼ 100,000 psi of Young's modulus). Thus, many reservoir management practices are based on trial and error methods which are sub-optimal. This work aims to enhance the efficiency of reservoir management activities.

The usage of Capacitance Resistance Model (CRM) has been increasing due to its simple but effective capabilities of analyzing waterflooding performances. However, CRM has innate limitations as well. The core calculation of CRM is solving nonlinear regression. Solution of nonlinear regression is not unique since it is not guaranteed to find the global minimum and is affected by solver algorithms and initial guesses. In addition to the innate limitations, due to the lack of bottomhole pressure data in the Lost Hills and its high oil viscosity (∼ 20 °API), the accuracy of Lost Hills CRM solution is not enough to be used in daily operations. Stochastic CRM (SCRM) was developed to mitigate these limitations by combining bootstrap with CRM and provides stochastic answers. SCRM estimates probabilities of an initial solution using bootstrap, substitutes low probable parameter values with P50 values, and updates injector-producer connection pairs and its interwell connectivity.

SCRM was developed for analyzing waterflooding operations such as identification of ineffective injector-producer connection pairs and estimation of reservoir pressure. SCRM analysis results were benchmarked against the Lost Hills tracer test data and demonstrated that SCRM provided a better solution than CRM. Compared to the fact that the deterministic solution from CRM found only 50% of connection pairs which tracer identified, SCRM solution identified 10 out of the 12 tracer identified connections. After the verification, SCRM was applied to find out connected injectors which cause Fluid Over Pump (FOP) wells. The existing workflow for identifying connected injectors was a trial and error method and hard to find connected injectors if connected injectors are located farther than 300 ft from FOP wells (chronic FOP wells). The novel workflow has been deployed so that FOP wells can be mitigated systematically and enable the optimization team to improve its reservoir management efficiency. In 2017, 10 chronic FOP wells were mitigated by identifying connected injectors with the novel workflow.
Salt Water Disposal Performance in the Williston Basin
Authors: Schmidt Darren , Miguens Andrea Carolina , Wong Clarence , Hlava Kimberly , Pinkston Daniel
Published: April 2019

A significant expansion has occurred in North Dakota to accommodate disposal of produced water since the onset of oil production from the Bakken petroleum system. Anywhere from 1-2 barrels of water are associated with each barrel of oil produced in the Williston Basin. The growth over the past 10 years warrants a closer examination of the reservoir in which we store produced water and the related injection well performance. A sample of well test data, and an investigation of average injection pressure, cumulative injection, and injectivity index suggest that poor injection performance is associated with limitations to reservoir quality. Historically good injection wells appear to maintain positive injection volumes and are not significantly limited by wells added nearby. Increases in reservoir pressure are evident over limited geographic areas. Wells in these areas tend to suffer lower injection rates, and higher average injection pressures. The evidence from well testing, current geologic investigations, and geographic well characteristics suggest that localized geologic properties and reservoir quality are the primary limiting factors for poor injectivity performance.
Analytical Scaling Enhances Production Analysis of Multi-Fractured Horizontal Wells
Authors: Lemoine Romain , Lee John
Published: April 2019

This paper presents a rigorous method to scale rate-time profiles of multi-fractured horizontal wells (MFHW) to a set of reference reservoir and completion properties. Scaling is required for development of accurate production forecasts and typical well production profiles (type wells) with minimum uncertainty.

We use a modified version of commonly-used type curves, notably the Wattenbarger type curve, to fit production data. The fit requires that production profiles exhibit a negative half slope during transient linear flow followed by negative unit slope during boundary-dominated flow on a rate vs. material balance time plot. The horizontal and vertical displacement required to fit observed data to the type curve define the scaling factors for individual wells.

We present a set of equations to scale a given well's production profile to that of a reference well with specified effective permeability, fracture length, lateral length, net-pay thickness, drawdown, and fracture stage spacing. Just as we can scale a group of wells to common reference conditions, we can also rescale to predict the performance of a well with specified properties, such as average properties determined from wells analyzed or wells with completion designs different from those analyzed. While it is common and clearly important to normalize (scale) rate profiles for lateral length, we demonstrate that it is also crucial to scale production profiles in rate and time to account for differences in permeability, fracture spacing and thus, the duration of flow regimes. We provide examples of successful scaling based on publically reported production data from Marcellus, Barnett, Niobrara, Midland Basin (Wolfcamp) and Eagle Ford resource plays.

Most of the methods used to assess the performance of MFHW's in resource plays rely on having a statistically significant number of analogs. However, datasets of sufficient size are often either unavailable or limited by the large variety of completion designs and well performance characteristics. Our approach to scale production can dramatically increase the number of analogs available to characterize a geologically similar area and thus reduce the uncertainty in production forecasts.
Application of Novel Surfactants with Co-Solvent Character for Heavy Oil Recovery
Authors: Baek Kwang Hoon , Argüelles-Vivas Francisco J. , Abeykoon Gayan A. , Okuno Ryosuke , Weerasooriya Upali P.
Published: April 2019

A new class of ultra-short hydrophobe surfactants with co-solvent character was investigated as a sole additive to conventional polymer flooding for heavy oil recovery. No alkali was used for emulsification. The surfactants tested are composed of a short hydrophobe (phenol in this research) extended by a small number of propylene oxide (PO) and sufficient ethylene oxide (EO) units to achieve aqueous stability: phenol-xPO-yEO. Results are presented for the selection of ultra-short hydrophobe surfactants, aqueous stability, emulsion phase behavior, and oil-displacement through a glass-bead pack at 368 K.

Results show that 2 wt% phenol-4PO-20EO was able to reduce the interfacial tension between oil and NaCl brine to 0.39 dynes/cm, in comparison to 11 dynes/cm with no surfactant, at 368 K. Water flooding, 70-cp polymer flooding, and surfactant-improved polymer flooding were conducted for displacement of 276-cp oil through a glass-bead pack that represents the clean-sand faces of a heavy oil reservoir in Alberta, Canada. The oil recovery at 2 pore-volumes of injection was 84% with the surfactant-improved polymer flooding, which was 54% and 22 % greater than the water flooding and the polymer flooding, respectively. Results suggest a new opportunity of enhanced heavy oil recovery by adding a slug of one non-ionic surfactant with co-solvent character to conventional polymer flooding.
Improving Value of History Matching by Bridging the Discipline Gap with Integrated Static and Dynamic Subsurface Evaluations
Authors: Fjerstad Paul A. , De La Colina Julio C. , Turner Alexandre , Tyshkanbayeva Aigul , Pusca Victor , Lolomari Otonye T. , Ayanbule BabaFemi , Kim Jong Uk , Ghoraishy Mojtaba , Chukwuka Clement
Published: April 2019

This paper describes an alternative practical interdisciplinary collaboration and application of a work process applied to field case studies from recent producing fields for identification of field development opportunities. Multi-disciplinary integration of static and dynamic work processes is part of the history matching process. The process improvements involve use of a common visualization environment that enable efficient iterative updates to reservoir characterizations and modification of production engineering information.

Next generation subsurface modeling tools and reservoir simulation technology has been deployed and adopted. Modeling tools continue to evolve and mature. Geologists, geophysicists and reservoir engineers now have access to user-friendly tools with common look-and-feel graphical user interfaces. The workflow outlined in this paper is one possible workflow enabled using a flexible and integrated framework. The primary goal of modeling is to streamline the construction and practical business use of reservoir models. The introduction of interdisciplinary work processes achieves this goal. Drillers, petroleum and reservoir engineers and geoscientists are all working from the same subsurface depth model, co-visualizing and co-analyzing diverse types of information in a collaborative environment.

The history matching process and workflow requires updates and adjustments to the dynamic model. A typical history match starts with hand-over of the static model to the reservoir engineer. This process oftentimes results in a dynamic model with a lack of ongoing direct updates of the static geological model and hence loss of full evaluation of all geological uncertainties. The loss of integration between the static and dynamic modeling results in too much time spent modeling of detailed geological events that have little impact on the dynamic behavior of the reservoir. Missing important geological and petrophysical parameters may have significant impact on the history match quality. Direct changes and updates to the static reservoir description ensures consistency between the static and the dynamic models.

Results from dynamic modeling combined with an update of the reservoir characterization can easily be shared with all team members. This process improves the quality of matched models, it reduces the speed of completing history matches and results in improved understanding of the static and dynamic uncertainties and their interdependencies. Discussion of complex relationships with the entire team observing an array of data and interpretations, results in clearer communication and enhanced decision making.
Uncertainty Analysis in Production Forecasting-Part II: A Case Study on the Barnett and Haynesville Shale Plays
Authors: Mabadeje Ademide O. , Ghanbarnezhad Moghanloo Rouzbeh
Published: April 2019

This paper evaluates the impact of decision making and uncertainty associated with production forecast for 11000+ wells completed in the Barnett & Haynesville shale plays. Existing studies show that unconventional reservoirs have complex reservoir characteristics making traditional methods for ultimate recovery estimation insufficient. Based on these limitations, uncertainty is increased during the estimation of reservoir properties, reserve quantification and, evaluation of economic viability. Thus, it is necessary to determine and recommend favorable conditions in which these reservoirs are developed.

In this study, cumulative production is predicted using four different decline curve analysis (DCA) - power law exponential, stretched exponential, extended exponential and Duong models. A comparison between the predicted cumulative production from the models using a subset of historical data (0-3months) and actual production data observed over the same time period determines the accuracy of DCA's; repeating the evaluation for subsequent time intervals (0-6 months, 0-9 months,..) provides a basis to monitor the performance of each DCA with time. Moreover, the best predictive models as a combination of DCA's predictions is determined via multivariate regression. Afterwards, uncertainty due to prediction errors excluding any bias is estimated and expected disappointment (ED) is calculated using probability density function on the results obtained.

In this paper, uncertainty is estimated from the plot of ED versus time for all wells considered. ED drops for wells having a longer production history as more data are used for estimation. Also, the surprise/disappointment an operator experiences when using various DCA methods is estimated for each scenario. However, it appears that in both plays power law exponential serves as the lower boundary of the forecast whilst the upper boundary – stretched exponential (SE) and Duong (DNG) method always significantly overpredicts the cumulative production in the Barnett and Haynesville respectively.

The outcome of the paper will help improve the industry's take on existing uncertainty in production forecast using the concept of expected disappointment. This study suggests that effects of bias due to decision making can be much greater than what has often regarded, which can change the performance evaluation of the Barnett and Haynesville plays in terms of economic feasibility.
Feasibility Study of Heavy oil Recovery Using In-situ Steam Generated by Thermochemicals
Authors: Moussa Tamer , Patil Shirish , Mahmoud Mohamed
Published: April 2019

Alaska North Slope (ANS) contains heavy oil (12-23 API) with an estimated range of original oil in place (OOIP) of 13 to 25 billion barrels. This resource has been considered as one of the largest heavy oil deposits in the United States. However, several technical challenges are limiting its commercial development. One of the most significant difficulty is the overlying 1,800-2,000 ft-thick permafrost layer, which causes unavoidable significant heat losses when steam is injected from the surface steam generators, and the potentially disastrous effects due to melting of the permafrost around the cemented casing. Therefore, surface steam injection might not be a viable option to develop this resource, although it is the most commonly used approach of heavy-oil recovery. Hence, the objective of this research is to conduct a feasibility study on the application of new approach, in which steam is generated downhole using thermochemical reaction (SGT) combined with steam assisted gravity drainage (SAGD), to recover heavy oil from Ugnu reservoir which is one of the major oil deposits in ANS.

A numerical simulation model for Ugnu heavy oil reservoir is built using CMG-STARS simulator. Then a MATLAB framework is integrated with the simulation model to study different recovery strategies on the project profitability. Net Present Value (NPV) is used in this study as the key performance indicator while monitoring oil recovery factor (RF) and cumulative oil production (COP). The design and operational parameters studied and optimized in this paper involve; 1) well configurations and locations, 2) steam injection rate and quality, steam trap and startup heating period to initialize SAGD process.

The results show that the in-situ SGT is a successful approach to recover heavy oil from Ugnu reservoir and it yields high project profitability, in terms of the NPV after 10 years of development. The main reason of this outperformance is ability of SGT to avoid the significant heat losses and associated costs, in the surface steam injection methods.

This paper introduces a novel approach to generate downhole steam using thermochemical reactions to overcome the challenges associated with heavy-oil resource development from Ugnu reservoir, while minimizing the environmental impact by reducing the greenhouse gas emission related to surface steam injection methods.
Coke Deposition During Air Injection Assisted Cyclic Steam Stimulation Process: Mechanism Study and Field Impact Analysis
Authors: Wang Yanyong , Zhang Liang , Ren Shaoran
Published: April 2019

Air injection assisted cyclic steam stimulation (CSS) is an innovative and effective process for enhancing ultra heavy oil recovery and increasing the efficiency of steam injection, which has been successfully applied in over 200 wells in Liaohe oilfield (Northeast China) in recent years. During this process, low temperature oxidation (LTO) and pyrolysis of crude oils may take place spontaneously under elevated reservoir temperatures (around 300°C) due to steam and air coinjection. There have been concerns over the formation and deposition of coke-like substance in the reservoir and their impacts on reservoir permeability and oil production.

In this study, the mechanisms of coke formation during this process were investigated based on experimental results, and the effects of LTO reactions on coking and oil pyrolysis were analyzed. A mechanistic model of coke formation in the presence of air was constructed, in which the coking process was modeled based on the partial equilibrium reaction. The model was then incorporated into a reservoir simulator, and a field scale reservoir simulation study of this process was conducted in order to reveal the impacts of coke deposition on formation properties and oil recovery performance.

The simulation results demonstrate that coke deposition can reduce the fluid porosity and permeability in the near well region, which will induce a detrimental effect on heavy oil production. Therefore, the possible reduction of formation permeability due to precipitation of coke-like substance should be considered. The field performance of this technique conducted in a typical ultra heavy oilfield was simulated and presented along with the analysis of the possible coking effect. Injection of air with reduced oxygen content is proposed for reducing the coking effect, and the simulation results show that injection of air with oxygen content of 10 vol% will be beneficial to retarding coke formation and deposition, and moreover the safety hazard of explosion will also be eliminated in field operation.

This study can provide new insights into the numerical modeling of the coking process and deepen the understanding of the air injection assisted CSS process for extracting oil from ultra heavy oil reservoirs.