Moreno Ortiz, Jaime Eduardo (Schlumberger) | Gossuin, Jean (Schlumberger) | Liu, Yunlong (Schlumberger) | Klemin, Denis (Schlumberger) | Gurpinar, Omer (Schlumberger) | Gheneim Herrera, Thaer (Schlumberger)
Challenges on EOR process upscaling have been discussed extensively in the industry and effects of diffusion, dispersion, heterogeneity, force balance and frontal velocity -among others, recognized and qualified, along with the importance of understanding the numerical model finite difference equations and modeling strategy. Augmenting the upscaling complexity is the often-limited understanding/data on the EOR displacement at different scales (from micro to full field), including the EOR agent/rock/fluid interactions that is often available at the early stages of the EOR process de-risking.
A common denominator for the EOR process characterization and upscaling (along with the discretization of the displacement) is the non-uniqueness nature of the problem. As the complexity of numerical representation of the EOR process increases (thus increasing data characterization requirements), so does the number of plausible solutions and challenges when dealing with an otherwise incomplete dataset. Digital rock has evolved as a strong alternative to complement laboratory corefloods, allowing for EOR agent optimization on a high-resolution digital representation of the pore structure, detailed digital fluid model of both reservoir fluids and EOR agents and physical rock-EOR agent-reservoir fluid interaction, thus providing several calibration points to ensure the finite-difference model calibration and upscaling preserve the process behavior.
This paper discusses the use of digital rock solutions on the EOR deployment, particularly on translating the results to numerical finite difference models, addressing the inherent laboratory measurement uncertainty and proposing a fit-for-purpose multi-scale upscaling strategy that addresses both effects of heterogeneity and EOR agent characterization during the upscale process.
This paper addresses the challenges of chemical flooding upscaling, particularly polymer by using a real-life polymer injection case where digital rock, corefloods and more importantly pilot results are available to test and validate our observations. Using a polymer coreflood and digital rock results as input, numerical finite difference simulation models were built and calibrated to effectively reproduce the displacement physics observed on both digital rock and corefloods, digital flood results were used to bridge the laboratory-to-numerical model step by providing effective upscaled polymer properties as well as intrinsic rock properties such as relative permeability and capillary pressures, which are then taken through a series of multi-scale finite difference models to identify, validate and quantify upscaling requirements, addressing polymer deformation through pore throats and effective simulation viscosity. Digital rock is used to rank and resolve ambiguity on the finite difference model calibration by providing an otherwise rare opportunity to visualize the displacement in the 3D space. The analysis shed a new light on fluid-fluid and fluid-rock interaction at pore scale and enabled us to improve on the finite difference model generation and polymer properties.
Green fields today mostly can be regarded as marginal fields and successfully developed. It covers the complete assessment of the oil and gas recovery potential from reservoir structure and formation evaluation, oil and gas reserve mapping, their uncertainties and risks management, feasible reservoir fluid depletion approaches, and to the construction of integrated production systems for cost effective development of the green fields. Depth conversion of time interpretations is a basic skill set for interpreters. There is no single methodology that is optimal for all cases. Next, appropriate depth methods will be presented. Depth imaging should be considered an integral component of interpretation. If the results derived from depth imaging are intended to mitigate risk, the interpreter must actively guide the process.
Heavy oil production poses multiple challenges on oil companies such as intricate operations (complexity), high operational costs (efficiency control), and solutions for high viscosity and low API fluids (specific technology). This paper describes the technical workflows implemented in a heavy oil field located in the Middle Magdalena Valley basin in Colombia to assist in the complexity of an operation where cyclic steam injection is applied. The complexity of producing heavy oil is due to its high viscosity at repository conditions, which limits the mobility of the fluid and the draining effect to a relative small area around the wellbore, thus it is required an infrastructure that involves many wells, flowlines, manifolds, and facilities to produce this type of crude oil. To support the surveillance and the technical decision-making processes in an operation with more than 300 wells, effective workflows were designed and implemented with the aims to eliminate mistaken decisions, optimize resources, and contribute to cost optimization. The algorithms, foundation of these workflows, are presented with the analysis of different elements taken into consideration during the technical design process, such as well intervention program, field infrastructure, daily reports, and current well parameters. Additionally, four specific targets are discussed: Heat injection surveillance, which follows program plan vs current execution, including the calculation of heat values from operational conditions (pressure, steam quality, mass rate, and running time); Well test schedule, which organizes the wells test plan in a hierarchy considering flowline connections, well services plan, and priority well list (time since last test, wells with abnormal behavior); Dinalog plan, which is the foundation for artificial lift control; Steam injection scheme, which creates a suggested ranking of wells requiring steam stimulation based on current conditions (Wcut, WHT, production rate), time since last stimulation, and steam/oil ratio. The developed workflows are applicable in both heavy oil fields, and light oil fields with a large number of wells, and they can be a valuable foundation for digital oil fields providing support for technical management and contributing to resolve the challenges of a vast operation.
Previous experimental studies show that nanoparticle-stabilized supercritical CO2 foams (or, NP CO2 foams) can be applied as an alternative to surfactant foams, in order to reduce CO2 mobility in gas injection enhanced oil recovery (EOR). These nanoparticles, if chosen correctly, can be an effective foam stabilizer attached at the fluid interface in a wide range of physicochemical conditions.
By using NP CO2 foam experiments available in the literature, this study investigates the applicability of NP foams for mobility control and thus improved sweep efficiency. This study consists of two tasks: (i) presenting how a population-balance mechanistic foam model can be used to fit experimental data and determine required model parameters, and (ii) examining sweep efficiency in a condition similar to Lisama Field (a 5-spot pattern with 4 producers and 1 injector in the middle), by using relevant gas mobility reduction factors derived from mechanistic modeling technique. The field-scale simulations are conducted with CMG software, contrasting NP and surfactant foams (in both dry and wet foam injection conditions) to gas only injection and gas-water coinjection (no foam).
The results show how the model can successfully reproduce coreflood experimental data, creating three different foam states (weak-foam, strong-foam and intermediate states) and two steady-state strong-foam regimes (high-quality and low-quality regimes). When the gas mobility reduction factors ranging up to 10 from the model fit are applied in the field-scale simulations, the use of nanoparticles improves oil recovery compared to gas-water co-injection, but not as efficient as successful surfactant foam injection does. This implies that although nanoparticle-stabilized foams do provide some benefits, there still seems some room to improve stability and strength of resulting foams.
Iturraran-Viveros, Ursula (Facultad de Ciencias, Universidad Nacional Autónoma de México (UNAM)) | Muñoz-García, Andrés M. (Instituto de Minerales CIMEX, Universidad Nacional de Colombia, Medellín) | Parra, Jorge O. (JPGeosciences, Helotes, Texas, USA)
SUMMARY A common application in seismic imaging of machine learning algorithms (Artificial Neural Networks) is to produce petrophysical models at seismic scale combining well-log information and seismic data. Here we use these resulting models as prior inputs in full-waveform inversion (FWI). We compute instantaneous seismic attributes to a stacked P-wave reflected seismic section in the Tenerife field located in Colombia and train Artificial Neural Networks (ANN's) to estimate P-wave velocity V The logs are provided by a well near the survey line, allowing images of different rock properties to be used in the inversion of velocities. This process allows us to build an initial estimate of the earth property model, which is iteratively refined to produce a synthetic seismogram (by means of forward modeling) to match the observed seismic data. A nonlinear least-squares inversion algorithm minimizes the residual (or misfit) between observed and synthetic full-waveform data improves the P-wave velocity resolution.
Presentations Key Parameters Affecting Reservoir Wetting in Carbonate and Sandstone Reservoirs Tina Puntervold, Smart Water EOR Group and Skule Strand, University of Stavanger Concepts, Screening, and Laboratory Studies for Chemical EOR Lirio Quintero, Baker Hughes, a GE Company 10:00 - 10:30 Coffee Break 10:30 - 12:00 SESSION 2: Water Flooding and Benefits of Smart Water EOR Processes Session Chairpersons Skule Strand, University of Stavanger; Francisco Porturas, ScanViz Fishbones; Jose Luis Bashbush, Schlumberger This session will address benefits of optimized water flooding in sandstone and carbonate reservoirs, departing from fundamental understanding of Smart water EOR processes, from modelling, implementation and current status. Presentations Recent Research updates on Smart Water EOR Processes in Carbonate and Sandstones Tina Puntervold, Smart Water EOR Group and Skule Strand, University of Stavanger Water Fooding Pilot - Block 61 (Shaya) Claudio Marcelo Fonseca, Schlumberger Low Salinity Water Injection Optimization in the Namorado Field Using Compositional Simulation and Artificial Intelligence Argenis Alvarez, CMG 12:00 - 13:30 Lunch 13:30 - 15:00 SESSION 3: Discussion and Review of Thermal EOR Processes Session Chairpersons Felix Ascanio, Independent Consultant; Diana Mercado, Computer Modelling Group; Mariela Araujo, Sheller In this session we focus on the application of thermal methods for heavy oil field development, performance improvement for cyclic steam stimulation (CSS), steamflood and Steam Assisted Gravity Drainage (SAGD) technologies, application of any novel hybrid thermal process associated with in-situ combustion, as well as the implementation of HPHT testing and surveillance monitoring. This session will also discuss the state of the art technology related to thermal screening, HPHT lab experiments, and current thermal project piloting and development in Colombia and Canada. Presentations Hydraulic Fracturing Effect in Oil Recovery During a Cycling Steam Injection Argenis Alvarez, CMG Nare Colombian Field Preformed Foam Injection Hector Rodríguez, Ecopetrol Thermal Recovery in Carbonate Naturally Fractured Reservoirs: Theory and Applications Reza Mehranfar, Schlumberger 15:00 - 15:30 Coffee Break 15:30 - 17:00 SESSION 4: Good and Bad Practices During EOR Evaluation Session Chairpersons Eduardo Manrique, Ecopetrol; Khosrow Biglarbigi, INTEK; Jose Bashbush, Schlumberger Enhanced oil recovery implementation is very complex and successful applications need to be tailored to the reservoir properties. A systematic evaluation and development process is required to screen, evaluate, pilot test, and apply EOR processes for particular applications.
The last decade has spotted a tremendous upsurge in casing failures. The aftermaths of casing failure can include the possibility of blowouts, environmental pollution, injuries/fatalities, and loss of the entire well to name a few. The motivation behind this work is to present findings from a predictive analytics investigation of casing failure data using supervised and unsupervised data mining algorithms. Scientists and researchers have speculated the underlying causes but to date this type of work remains unpublished and unavailable in the public domain literature.
This study assembled comprehensive data from eighty land-based wells during drilling, fracturing, workover jobs, and production. Twenty wells suffered from casing failure while the remaining sixty offset wells were compiled from well reports, fracturing treatment data, drilling records, and recovered casing data. The failures were unsystemic but included fatigue failure, bending stresses from excessive dogleg, buckling, high hoop stress on connections, and split coupling. The failures were detected at various depths, both in cemented and uncemented hole sections. Failures were spotted at the upper and lower production casing.
Using a predictive analytics software from SAS, twenty-four to twenty-six variables were evaluated through the application of various data mining techniques on the failed casing data sets. The missing data was accounted for using multivariate normal imputation. The study outcome addressed common casing sizes and couplings involved with each failure, failure location, hydraulic fracturing stages, cement impairment, dogleg severity, thermal and tensile loads, production-induced shearing, and DLS. The predictive algorithms used in this study included Logistic Regression, Hierarchal Clustering, and Decision Trees. While the descriptive analytics manifested in visual representations included Scatterplot Matrix, and PivotTables. Failure causes were identified. A total of five statistical techniques using the aforementioned algorithms were developed to evaluate the concurrent effect of the interplay of these variables. Nineteen variables were believed to possess the highest contribution to failure. Scatterplot matrix suggested a complex correlation between the total base water used in fracturing simulation and casing thickness. Logistic Regression suggested nine variables were significant including: TVD, operator, frac start month, MD of most severe DL, heel TVD, hole size, BHT, total proppant mass, cumulative DLS in lateral and build sections variables as significant failure contributors. PivotTables showed that the rate of casing failure was highest during the winter season.
This investigation is aimed to develop a thorough understanding of casing failures and the myriad of contributing factors to develop comprehensive predictive models for future failure prediction via the application of data mining algorithms. These models intend to provide a theoretical and statistical basis for cost-effective, safe, and better drilling practices.
Located in the Middle Magdalena River Valley basin, in the department of Santander, municipality of Barrancabermeja in the rural area of El Centro. La Cira-Infantas is the oldest Field in Colombia and with it, the oil industry was born in Colombia. It has proven reserves of 172 MMBOPD, it reached a production of 65000 barrels in 1939 until it declined to 5000 BOPD in 2005. Through an association contract between two operators, looking for the implementation of new technology, in 2017 45000 BOPD were obtained.
During its operation and through the implementation of the secondary recovery method in the field, a high gas and sand content was identified as a problem for high fluid production wells. This has generated premature flailures in the artificial lifting system with Progressing Cavity Pumps during the production of the Arenas C interest zone that raises the costs to the point that makes them economically nonviable. According to the needs of the field and looking for new and better solutions, the design and application of a pump with a special geometry that allowed giving viability to the operation of these problem wells, was performed, thus expanding their run life and reducing costs associated to their intervention. The implementation of this type of pump has allowed a 63% reduction in installation, maintenance and operation costs, and 86% in differed and production loss costs; in general, a 67% economic benefit versus the conventional system was obtained providing technical and economic viability to the development of these reserves.
Vargas, A. F. (Pump Best Services Colombia) | Duran, J. (Ecopetrol SA) | Simpson, A. (Veretek) | Santos, R. (Schlumberger) | Doval, J. M. (Ecopetrol SA) | Muñoz, L. (Schlumberger) | Patino Jerez, A. E. (Schlumberger Surenco S.A.) | Rativa, C. (Ecopetrol, SA) | Hernandez, N. (A. Ecopetrol SA) | Rozo, Rozo (Ecopetrol SA) | Rios, D. (Ecopetrol SA)
This paper presents a successful application and the lessons learned during a pilot test under which a new electrical submersible pumping technology was installed in 4 wells. These helico-axial downhole pumps, V-Pump, were installed under a program of new technologies testing, which aimed for artificial lift run life extension in an extremely high sand-producing field under current cost constraints.
The oil price turndown forced Casabe Field to leave some wells inactive, even though they still have significant reserves. The cause of this decision was the expenses associated to the high frequency of interventions required due to the adverse sand production effects on the artificial lift systems.
Due to the low run life of conventional artificial lift systems that are customary to use in the field, it was necessary to search for emerging technologies that would meet the challenge presented. A screening process for new technologies were conducted, and after that, these pumps were installed in four wells, which were continuously monitored with downhole temperature, vibration and pressure sensors, fluid levels measurement, VSD readings and production tests, which would allow to understand the technology performance to achieve the desired run life, oil production gain, and to obtain lessons learned to design the second phase of the testing project.
The use of this innovative pumping technology extended the run life in the pilot wells between 180% and 420%, allowing the production of their remaining oil reserves, and giving a new approach in the production strategy of the field. One well is still running after 13 months.
Also, based on the on the information collected during the well production phase, through downhole sensors and VSD parameters, and the findings during the pump's dismantle, some recommendations were made to improve the performance in the second phase of the project. Recommendations include both improvements in the pump design and to the screening process of candidate wells.
This current paper is intended to show the implemented methodology for integrated mineralogical, geochemical, petrophysical characterization of Shale Plays from the analysis of well cuttings at the Colombian Petroleum Institute (ICP).
The implemented methodology starts with taking drilling cuttings (Wet Trench samples) during the drilling of exploratory wells in areas of interest for production of Shale Oil & Gas in diferents Colombian basins. Then fragments are selected (picking) with stereoscopic magnifiers. Observed proportions and lithology in the Formation Evaluation Log (FEL) for a given range should be consistent.
Subsequently, the textural and compositional macroscopic description of each sample using Hydrochloric Acid (HCL) to identify carbonates is performed. This description takes into account the degree of effervescence and solid waste analysis. Finally, the percentages of every lithotype present per interval are defined, and this way samples are selected for evaluation.
The evaluation of texture and composition of samples was performed by conventional Petrography of relative abundance of elements by means of Scanning Electron Microscopy (SEM). The mineralogical evaluation of samples is performed by X-ray Diffraction (XRD).
Furthermore, geochemical analysis of TOC and pyrolysis are performed in some fragments of the selected samples. Other tests include: Mercury Injection Capillary Pressure analysis (MICP), helium porosity, nanoindentation technique. These analyzes are made to determine mechanical properties of the rock. The integrated analysis of these techniques provides information to the mineralogical, geochemical and petrophysical characterization of rocks from a shale plays.
This allows defining areas of interest for hydraulic fracturing and production in a UnConventional Reservoirs. The methodology was validated with results obtained from core samples from well Iwana-1 drilled by Ecopetrol in unconventional reservoirs in Middle Magdalena Valley Basin (MMVB). This fact provided competitive advantage to Ecopetrol in exploration and exploitation of Shale Plays. This mineralogical, geochemical and petrophysical characterization laboratory methodology for Shale Plays from well cuttings was used during 2014 at the ICP to characterize 880 ft at El Tablazo Formation in well Casabe K1, 850 ft at La Luna formation in well Golosa 1 and 5,900 ft at Gala 1K at the same formation. This methodology allowed shortening the laboratory analysis time from 120 to 60 days with respect to laboratory tests on a core of 800 ft