bluuebunny/crossref_metadata_2025 huggingface dataset:
Corporate Engineering Center Org. Transformation in Response to New Business Challenges
Authors: Oshmarin Roman , Isakov Kirill , Chekanov Ignat , Taratin Nikolay , Shashel Vadim , Ignatyuk Anna , Vashkevich Alexey
Published: September 2021

Objectives/Scope

The world is changing rapidly. In order to response to VUCA conditions, we started the business transformation of GPN scientific and technical center (STC) in the mid 2019, and finished shortly after COVID crisis began (in June 2020). Now we can sum up the ultimate effect:

Methods, Procedures, Process

GPN STC made a long way since 2007 and became a strong corporate engineering center, providing a full range of services from the basin modeling to the integrated modeling. In 2019, we started the transformation from the description of objectives, and for these purpose, the survey of different business branches was performed. After that, we defined the shortcomings of the existing model (which was actually inside the organizational and administrative area), such as:

The transformation met all the challenges and made dramatic changes in the area of management and processes: We transformed STC works catalogue to product line and shift from instruments (such as geomodel) to business value (such as exploration strategy, based on geomodel). Now we focus on integrated analytical framework in support of key business decisions, rather than methodsor processes.The above shifting requires new roles and competences, thus we completely rebuild role model and staffing table. We initiated new role of account manager for every internal business customer, that is typically used in service companies, not in-house centers, and here we saw fantastic results and received positive feedback from business. The new role of discipline leader helped to increase speed of team gathering for new projects from average 7 weeks to 3-4 weeks;We removed 2 levels of hierarchy and moved on to "flattened" organizational structure;We initiated the internal business consulting team, responsible for implementation all of the conceptual decisions (which will be a new service for internal business customers in future);The single-contract principle was suggested, and the orders inside of this according to product line were initiated, where account manager is the person, responsible for implementation of this contract;Product transformation was supported by organizational agile transfrormation for cross-functional teams (Mohamed Saeed AlMarar, 2019);And a lot of another important changes (which will be described in final presentation);

Results, Observations, Conclusions

It is important to highlight again, this deep and ambitious transformation allowed STC to obtain sustainable target indexes/KPIs and business results:

Novel/Additive Information

We were the first (at least in Russian O&G industry), who shifted the entire corporate engineering center for product model, with focus on business value and now we perform strong operationalization of concept in order to push all changes into real life.
Modern Look at Uncertainty in Conceptual Geological Modelling. Development of the Decision Support System for Petroleum Exploration
Authors: Chirkunov Kirill , Gorelova Anastasiia , Filippova Zoia , Popova Oksana , Shokhin Andrey , Zaitsev Semen
Published: September 2021

At the early stages of field life, the subsurface project team operates under lack of information. Due to the high uncertainties, decisions at the exploration and appraisal stages are often influenced by cognitive distortion that leads to overestimation or underestimation of hydrocarbon reserves and, as a result, to suboptimal investment decisions.

World practice allows us to identify the most common causes of cognitive bias: the team focus on the most provable according to their view scenario and may ignore data that contradicts the chosen scenario,the opinions of the team members differ in the choice of the most likely scenario,the team members work with geological and geophysical (G&G) data performing separate tasks and may miss important connections between various sources of information.

The consequences of these cognitive distortions cause an increase in risk capital, the duration of exploration activities, and the choice of suboptimal field developmentstrategy resulting in a decrease in the effectiveness of the exploration program and the project as a whole.

To reduce such risks, it is possible to attract subject matter experts with extensive experience to support the project team. But the amount of experts is limited and this approach cannot be implemented for the entire portfolio of exploration projects.

As result of a research project of Gazpromneft in a partnership with IBM Research, an innovative approach was developed for the objective integration of geological and geophysical data. The main idea of this approach is to support the geologist's decisions by an intelligent assistant working on the principles of the modern theory of knowledge engineering. Using the generalized expert knowledge, the intelligent assistant impartially integrates disparate geological information into a set of conceptual geological models (scenarios, objectively evaluates their probabilities, and helps to plan optimal exploration/appraisal activities.
Development and Application of Fast Simulation Based on the PSS Pressure as a Spatial Coordinate
Authors: Nakajima Kenta , King Michael
Published: September 2021

Recent studies have shown the utility of the Fast Marching Method and the Diffusive Time of Flight for the rapid simulation and analysis of Unconventional reservoirs, where the time scale for pressure transients are long and field developments are dominated by single well performance. We show that similar fast simulation and multi-well modeling approaches can be developed utilizing the PSS pressure as a spatial coordinate, providing an extension to both Conventional and Unconventional reservoir analysis.

We reformulate the multi-dimensional multi-phase flow equations using the PSS pressure drop as a spatial coordinate. Properties are obtained by coarsening and upscaling a fine scale 3D reservoir model, and are then used to obtain fast single well simulation models.

We also develop new 1D solutions to the Eikonal equation that are aligned with the PSS discretization, which better represent superposition and finite sized boundary effects than the original 3D Eikonal equation. These solutions allow the use of superposition to extend the single well results to multiple wells. The new solutions to the Eikonal equation more accurately represent multi-fracture interference for a horizontal MTFW well, the effects of strong heterogeneity, and finite reservoir extent than those obtained by the Fast Marching Method.

The new methodologies are validated against a series of increasingly heterogeneous synthetic examples, with vertical and horizontal wells. We find that the results are systematically more accurate than those based upon the Diffusive Time of Flight, especially as the wells are placed closer to the reservoir boundary or as heterogeneity increases.

The approach is applied to the Brugge benchmark study. We consider the history matching stage of the study and utilize the multi-well fast modeling approach to determine the rank quality of the 100+ static realizations provided in the benchmark dataset against historical data. The multi-well calculation uses superposition to obtain a direct calculation of the interaction of the rates and pressures of the wells without the need to explicitly solve flow equations within the reservoir model. The ranked realizations are then compared against full field simulation to demonstrate the significant reduction in simulation cost and the corresponding ability to explore the subsurface uncertainty more extensively.

We demonstrate two completely new methods for rapid reservoir analysis, based upon the use of the PSS pressure as a spatial coordinate. The first approach demonstrates the utility of rapid single well flow simulation, with improved accuracy compared to the use of the Diffusive Time of Flight. We are also able to reformulate and solve the Eikonal equation in these coordinates, giving a rapid analytic method of transient flow analysis for both single and multi-well modeling.
Making Workovers Easy and Cost Effective: Turning Old Ways into New Opportunities
Authors: Raza Mustansar , Elmoneim Hossam , Looten Kris , Elzanaty Omar , Shakeel Ahmed , Shehzad Kamil , Sarbast Mustafa , Yousif Serwer
Published: September 2021

A case study and methodology is presented to shed the light on the different processes followed during the placement of a non-damaging isolation barrier in a group of highly naturally-fractured and vugular gas wells. The temporary isolation aims at isolating the wellbore from the troublesome formation and allow the removal of the original completion string and install a new redesigned one. The process helped putting the wells back on production with-out the need to stimulate any of them. This helped client to reduce the overall workover cost by 40% and proved to be successful and efficient to complete the required operation in a time-efficient.

The operator had 4 wells with OH sections ranging from 40-80m which were completed in the late 1990's with no production packer. To preserve wellbore integrity the completion string needed to be pulled and replaced by a string with production packer and DH gauges. Visco-Elastic Surfactant (VES) and calcium CaCO3 (carbonate) used ubiquitously in field operations were tested for optimal design to fill highly fractured OH without damaging formation. Caliper logs were not available, and the presence of natural fractures posed a challenge to calculate the actual OH volume. A system was developed to carry the CaCO3 into the wellbore in stages and slickline was employed to measure fill after each stage. Once the OH was filled with CaCO3 and well would support a fluid column coil tubing was used to place an acid-soluble cement plug in the short interval between casing shoe and end of tubing (6-9m). The paper describes the optimization process followed to tune the CaCO3 pads composition, gel composition, mixing and placement technique.

The first well in the campaign required more than 10 times the theoretical volume of CaCO3 to fill the open hole with multiple settling issues at surface. It was concluded the surfactant gel was likely carrying the CaCO3 into the fractures. The procedure was modified to tie in a line of breaker solution to the well head allowing sufficient viscosity of the fluid to carry the CaCO3 from surface but immediately lose viscosity and allow the CaCO3 to settle in the open hole without being carried into the formation. Specific coil tubing procedures were employed to allow the setting of ultra-short acid soluble cement plugs (<6m).

All wells were successfully isolated to allow the safe workover of the completion string and returned to production with no loss of gas flow, with-out the need to stimulate after the work over.

The campaign exhibited a new method of employing existing technologies to achieve the objective in a highly challenging and relatively new oilfield of Kurdistan. The campaign also demonstrated the benefit, in terms of saving time and cost because of extensive pre-execution planning.
Vertical Education Enhancement Approach to Meeting Emerging Skillset Needs in Oil and Gas Industry
Authors: Egarievwe Stephen U , Johnson Jamie A , Agbalagba Ezekiel O
Published: September 2021

Emerging technologies often bring new opportunities to enhance productivity and safety in the oil and gas industry. New technologies and opportunities often come with the challenges of workforce development to provide entry-level and current professionals with the necessary training and skillset. This paper presents a vertical education enhancement (VEE) model approach to providing emerging skillset needs in the oil and gas industry with emphases on curriculum continuous improvement and lifelong learning. The top new and emerging technologies that are critical to the future of the oil and gas industry in enhancing productivity and safety include Internet of Things (IoT), artificial intelligence, big data analytics, cloud computing, and 3D modeling/visualization. As part of the solution to train the oil and gas industry workforce to meet the challenges of adopting these technologies, the VEE model features a vertical education structure that encompasses outreach to K-12 education, recruitment, tertiary education, professional training, and lifelong learning. It has an interwoven fundamental structure consisting of curriculum and mentorship, partnerships with stakeholders (industry, government, and community), and research and funding. The VEE model has periodic assessment continuous improvement processes for identifying emerging technologies and new skillset needed to improve the workforce. These processes are like those practiced by accreditation bodies such Accreditation Board for Engineering and Technology (ABET), United Kingdom Accreditation Services (UKAS), and Offshore Petroleum Industry Training Organization (OPITO). Diversity to increase the participation of underrepresented minority groups and women in engineering would further increase the workforce. The novelty that the VEE model approach brings is the effectiveness in providing skillset training in new and emerging technologies for the oil and gas industry at all levels of workforce development. These include content infusion in existing courses, special-topic and specialized courses at senior and graduate levels, and professional development education and training through lifelong learning platforms.
A 20 Years Systemic Study of Drilling Practices in a Geothermal Venture Reveals Insightful Findings
Authors: AlMuhaideb Abdullah , Noynaert Sam
Published: September 2021

Geothermal drilling has increased in the recent years with the renewable energy initiatives. Geothermal plants provide more than 6% of California's electricity. A large sum from the development budget is consumed by the drilling. This paper systematically analyzes and reviews the drilling activities and operations in a geothermal venture in Hawaii for more than 20 years to enhance the drilling operations and save costs.

The paper starts by studying the geology of the area, which is located in an active volcanic region. Then, an extensive data collection was performed that went back to more than 20 years. The data was preprocessed and cleaned to be used in the analysis. The well designs were analyzed and the distribution of the drilling time was determined. After that, the performance of the geothermal drilling was benchmarked with the oil and gas drilling and the geothermal drilling in different parts around the world.

The geology of the area is challenging with basaltic formation and tectonic movements. Volcanic eruptions that leads to closing wells were encountered in the recent years. As for the drilling, six challenges were identified and deeply analyzed. These challenges include: lost circulation, stuck pipe, cementing, low rate of penetration (ROP), logistics issues, and safety concerns. Each of these challenges was intensely investigated and solutions were proposed. The benchmarking with the oil and gas industry and other geothermal drilling operations shows that the geothermal drilling operations can be enhanced significantly. This improvement in the drilling in the geothermal venture will result in huge cost savings.

A set of recommendations to improve the performance is presented as new organizational and workflow changes, analysis and elimination of nonproductive time (NPT), and novel engineering redesigns.
Determination of Methane Diffusion Coefficients in Live Oils for Tight Reservoirs at High Pressures
Authors: Yang Yibo , Regueira Teresa , Rodriguez Hilario Martin , Shapiro Alexander , Stenby Erling Halfdan , Yan Wei
Published: September 2021

Molecular diffusion plays a critical role in gas injection in tight reservoirs such as liquid-rich shale. Despite recent efforts on measuring diffusion coefficients at high pressures, there is a general lack of the diffusion coefficients in live oil systems at reservoir conditions relevant to the development of these tight reservoirs. The reported diffusion coefficients often differ in orders of magnitude, and there is no consensus on the reliability of the common correlations for liquid phase diffusion coefficients, such as the extended Sigmund correlation. We employed the constant volume diffusion method to measure the high-pressure diffusion coefficients in a newly designed high-pressure tube. The experimental method was first validated using methane + hexadecane and methane + decane, and then used to measure the methane diffusion coefficients in two live oils at reservoir conditions. The obtained data were processed by compositional simulation to determine the diffusion coefficients. The diffusion coefficients measured for methane + hexadecane and methane + decane are in agreement with the existing literature data. For methane + live oil systems, however, the diffusion coefficients estimated by the extended Sigmund correlation are much lower than the measured results. An over ten times adjustment is needed to best fit the pressure decay curves. A further check reveals that for live oil systems, the reduced densities are often in the extrapolated region of the original Sigmund model. The curve in this region of the extended Sigmund correlation has a weak experimental basis, which may be the reason for its large deviation. The estimates from other correlations like Wilke-Chang and Hayduk-Minhas also give very different results. We compared the diffusion coefficients in high-pressure oils reported in the literature, showing a large variation in the reported values. All these indicate the necessity for further study on accurate determination of high-pressure diffusion coefficients in live oils of relevance to shale and other tight reservoirs.
Real-Time Optimal Resource Allocation and Constraint Negotiation Applied to A Subsea Oil Production Network
Authors: Dirza Risvan , Skogestad Sigurd , Krishnamoorthy Dinesh
Published: September 2021

This paper considers the problem of steady-state optimal resource allocation in an industrial symbiotic oil production network, or in general, a large-scale oil production system network, where different organizations share common resources.

These allocation problems are typically solved in a distributed optimization framework, where the optimization problem is decomposed into smaller subproblems, a central coordinator is used to coordinate the different subproblems. However, the use of a central coordinator may introduce additional practical challenges, such as impartiality issues, or additional operating costs, which is undesirable even in the technological selection phase.

To eliminate the need for a central coordinator, this paper proposes a consensus-based optimal resource allocation, where each subproblem or organization is locally optimized, and the coupling constraints are negotiated among the different organizations over a fixed communication network with limited information exchange.

The proposed approach is applied to a large-scale subsea oil production system, where the different wells are operated by different organizations. The simulation results of the application show that the proposed approach can optimally allocate the shared resources.
Economic Evaluation of CO2 Capture, Transportation, and Storage Potentials in Oklahoma
Authors: DaneshFar J. , Nnamdi D. , Moghanloo R. G. , Ochie K.
Published: September 2021

Oklahoma is known for having ample sources of CO2, pipelines and sinks where for many decades, oil and gas operators were injecting CO2 into geological formations for EOR purposes. We utilized SimCCS, an economic-engineering software tool (DOE-NETL), to integrate infrastructure related to CO2 sources, pipeline, and geological formations. The approved tax incentive program by IRS (45Q) has motivated many oil and gas operators to participate in reducing CO2 concentration and minimizing global warming effect by collecting CO2 from various sources, select the best pipeline route and the safest location to inject into geological formation for EOR purpose or deep saline aquifer for sequestration.

This paper presents an economic evaluation of CO2 capture, utilization, storage (CCUS) into geological formation in the state of Oklahoma. Under this comprehensive approach, the process of capturing, transporting, and storing CO2 into geological or saline formations has been economically evaluated for different sites and routes utilizing an ad hoc simulation software (SimCCS) for integrated modeling of CCUS. The outcome of this paper determines the most optimal scenario using optimization algorithms embedded in SimCCS.

This case study will mitigate the CO2 sequestration approval process when operator apply for tax credit under 45Q program. Our work will assist oil and gas operators by comparing different scenarios based on utilizing existing infrastructure, making decision in building new transportation system or new injection well to benefit the approved tax incentive program at its maximum capacity. Moreover, the outcome of this work will shed lights into future legislation demands (locally and nation-wide) to maintain CCUS momentum after its initial implementation phase is concluded.
Effect of Inter-Particle Van Der Waals Attraction on the Stability of Pickering Emulsions in Brine
Authors: Hatchell Daniel , Song Wen , Daigle Hugh
Published: September 2021

Pickering emulsions are stabilized by solid particles that occupy the fluid-fluid interface, physically preventing coalescence. Their stability in brine, where interparticle electrostatic repulsion is negligible and van der Waals (vdW) attraction dominates, makes them attractive for applications in porous media. Recent studies postulate that inter-droplet particle networks assemble in brine and aid Pickering emulsion stability to coalescence. This work experimentally assesses the effect of increasing interparticle vdW attraction on particle network strength and emulsion stability.

We grafted 6 nm, 12 nm, and 20 nm silica nanoparticles with varying densities of polyethylene glycol (PEG) to prevent aggregation and dispersed them in either brine or deionized water (DI). We characterized the PEG-coated nanoparticles with thermogravimetric analysis and dynamic light scattering to determine PEG grafting density, diameter, and zeta potential. To generate oil-in-water emulsions, we sonicated dispersions of variable nanoparticle concentration and decane in equal volumes. We imaged the emulsions with microscopy and centrifuged them for 15 minutes at 5000 g of acceleration, using the volume of decane released after centrifugation as a measurement of emulsion coalescence to the applied force.

Nanoparticle characterization confirmed successful grafting of PEG to the silica surface. We compared trends in emulsion stability as a function of salinity and particle diameter to changes in the relevant interparticle forces described by extended Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. Analysis of microscopy images showed an increase in emulsion droplet diameter with decreasing nanoparticle concentration, salinity, and increasing nanoparticle diameter. Through centrifugation we observed that lower PEG grafting densities tended to produce more stable emulsions, suggesting that particles with high grafting densities and consequently high steric repulsion tended to repel and prevent formation of strong particle networks. Emulsions generated in DI coalesced more easily, indicating that electrostatic repulsion dominated relative to vdW attraction and that particle networks did not form. In brine, where electrostatic forces were screened out by counterions, the emulsions better resisted coalescence, consistent with the formation of a particle network. The strength of the network was inferred from the difference in emulsion stability to coalescence in DI and in brine. We measured a greater brine-DI stability difference of 3.7× for the larger 20 nm PEG-coated nanoparticles, compared with 3.3× and 2.2× for the 12 nm and 6 nm PEG-coated particles, respectively, further supporting the role of particle networks on emulsion stability.
Efficient Water Softening for Avoidance of Scales in Heavy Oil Steam Floods
Authors: Prakash Prakhar , Concienne Reid , Demayo Trevor , Towne Kirsten
Published: September 2021

Pigging of Once Through Steam Generators (OTSGs) indicated various types of scales, the most predominant of these being silicates of hardness causing ions. It was noted that scaling propensity can potentially go up with higher Steam Quality (SQ) as the reject stream gets concentrated with ions. However, models suggested that there are benefits of higher SQ in enhancing fuel savings (8%) and electricity savings (2%) when SQ was increased by 20%. The challenges of higher SQ were noted in terms of increased scaling tendency and therefore the need for improved softening. In Field D, the service cycle, the backwash cycle, and the brining cycle were optimized leading to a gain in throughput and reduction in salt consumption. Service cycle improvement gained 30 % to 130 % in throughput between two regenerations, backwash cycle improvement by fluidizing the bed to nearly 35% helped gain 10% in throughput, and reduction of brining cycle from 75 minutes to 48 minutes helped reduce salt consumption by 56% without impacting the throughput. In Field B, a six month pilot revealed that shallow shell resins where ion-exchange is more efficient due to inert core (better intra particle diffusion control) can enhance the throughput by 30% - 80% and simultaneously reduce the number of regenerations by 15 – 30%. Resin fouling is still a major challenge to contend with as oil can foul the resin and throughput can decline by 0.5 – 3 folds. In a plant operation, where there are multiple softener and brine vessels, there is a need to optimize them as a system. Reliability, Availability, and Maintainability (RAM) Models are used in Field C to a) Address equipment configuration optimization with impact on capital capacity expansion project scope b) Understand how net softwater delivery capacity was affected by increases in inlet hardness and c) Assess through a comparison scenario, if the large cost of addressing the valve issue in an upstream nutshell filter was worth the lost production opportunity related to unplanned downtime.
Aplicability of an Innovative and Light Seismic Approach to Monitor SAGD Operations in Surmont: A Blind Test
Authors: Brun Victoria , Morgan Elodie , Gerl Brad , Cardozo Luis , Batias Jeremie
Published: September 2021

Surmont is a heavy oil field located in northeast Alberta which is currently being developed by a joint venture between ConocoPhillips and Total using Steam Assisted Gravity Drainage (SAGD). To monitor the enhanced oil recovery process and caprock integrity, highly repeatable 4D seismic surveys using dynamite have been completed over the years. In order to maximize the value of information while controlling costs, a novel light seismic monitoring approach has been "blind-tested" on existing 4D data.

The concept requires the use of only one source and one receiver couple, optimally placed in the field to monitor one or several subsurface spots, using time redundancy to detect 4D changes in these zones of interest. Three spot locations have been defined by the client on a well pad for which the history was not provided. For each of these spots, specific series of seismic processing steps have enabled the identification of the optimum source/receiver locations. Then, these optimum raw seismic traces extracted from different 4D campaigns have been analysed to detect potential time shift changes in the selected horizon induced by the growth of the steam chamber.

Time-shift changes were plotted for all 3 spots. An increase was observed for one of the spots (Spot 3) from the first 4D monitor in 2010 up to the last monitor in 2015. An increase was also plotted between March 2013 and September 2013 for another spot (Spot 1), changes attributed to the dynamics of the steam chamber. On the contrary, spot 1 did not see any effect of the steam. These time-shift changes were then successfully cross-checked with temperature data from observation wells, confirming the qualitative variations attributed to the effects of the steam chamber evolution.

It demonstrated the viability of this innovative seismic and focused monitoring approach to monitor the evolution of the steam chamber in Surmont. This also paves the way for a simpler and yet reliable and cost-effective way of monitoring the evolution of the steam chamber to further optimize production and increase rentability.
Multi-Class Taxonomy of Well Integrity Anomalies Applying Inductive Learning Algorithms: Analytical Approach for Artificial-Lift Wells
Authors: Yakoot Mostafa Sa'eed , Ragab Adel Mohamed Salem , Mahmoud Omar
Published: September 2021

Well integrity has become a crucial field with increased focus and being published intensively in industry researches. It is important to maintain the integrity of the individual well to ensure that wells operate as expected for their designated life (or higher) with all risks kept as low as reasonably practicable, or as specified. Machine learning (ML) and artificial intelligence (AI) models are used intensively in oil and gas industry nowadays. ML concept is based on powerful algorithms and robust database. Developing an efficient classification model for well integrity (WI) anomalies is now feasible because of having enormous number of well failures and well barrier integrity tests, and analyses in the database.

Circa 9000 dataset points were collected from WI tests performed for 800 wells in Gulf of Suez, Egypt for almost 10 years. Moreover, those data have been quality-controlled and quality-assured by experienced engineers. The data contain different forms of WI failures. The contributing parameter set includes a total of 23 barrier elements.

Data were structured and fed into 11 different ML algorithms to build an automated systematic tool for calculating imposed risk category of any well. Comparison analysis for the deployed models was performed to infer the best predictive model that can be relied on. 11 models include both supervised and ensemble learning algorithms such as random forest, support vector machine (SVM), decision tree and scalable boosting techniques. Out of 11 models, the results showed that extreme gradient boosting (XGB), categorical boosting (CatBoost), and decision tree are the most reliable algorithms. Moreover, novel evaluation metrics for confusion matrix of each model have been introduced to overcome the problem of existing metrics which don't consider domain knowledge during model evaluation.

The innovated model will help to utilize company resources efficiently and dedicate personnel efforts to wells with the high-risk. As a result, progressive improvements on business, safety, environment, and performance of the business. This paper would be a milestone in the design and creation of the Well Integrity Database Management Program through the combination of integrity and ML.
Advanced Cement Mechanical Integrity for Thermal Wells
Authors: Vu Manh-Huyen , Bouhours Aurélien , Bouhours Julien , Bouchair Rym , Bois Axel-Pierre , Badalamenti Anthony
Published: September 2021

Ensuring wells’ cement mechanical integrity (CMI) is of paramount importance for the success of a thermal project. Failed cement sheaths can lead to loss of production, environmental pollutions, or even to well abandonment. Over time, CMI software applications have been developed to design wells that do not leak. However, their efficiency depends not only on if their equations are verified, but also on how the models are validated versus wells’ downhole conditions. Unfortunately, most CMI tool designers have focused on only verifying if the models are mathematically correct, checking what is the time required for a simulation, and improving how are the simulations reported to the user. Typically, little time is dedicated on validating that the correct model is used for the specific well. This foresight has led to non-predictive CMI tools, which do not allow optimizing well designs.

The authors have been involved for more than 15 years in developing and validating CMI models. They have shown the importance of simulating the cement hydration to evaluate the state of stress in the cement after it has set. They also have highlighted how the plastic behavior of the cement design can lead to opening micro-annuli at the cement-sheath's interfaces. Recently the authors have started theoretical work in the area of the cement integrity of high and ultra-high temperature wells and how these temperatures, either naturally occurring or induced, could affect the cement's mechanical integrity. The work has focused on modeling the increase in pore pressures, the opening of micro-annuli at the cement sheath's boundaries, and the phase changes which take place in the cement when it is heated to high temperature values. To date this work showed that heating cement up to 250°C can result in pore pressures larger than 100 MPa unless if the pore pressures can be released. This work has also identified three mechanisms that can lead to such release of pore pressures: 1) During cement hydration, due to the water consumption by the chemical reactions, 2) When a micro-annulus opens due to the large pore pressures, therefore allowing venting the pressures to the surface or to a downhole reservoir, and 3) When a change of phase occurs in the cement when heated to more than 110°C, as this leads to the creation of additional porosity in the cement. All this means that the cement sheath should not be simulated as a closed system, but rather as an open thermo-hydro-chemo-mechanics. How these features impact CMI has never been studied before even if they can explain why some cement designs lead to tight cement sheath and other to leaking ones. This paper highlights the work that has been done and when these conditions should be considered, and if it is feasible to design cement sheaths that do not fail, even at very high temperatures.
Automated Verification of Sidewall Core Recovery Depth using Borehole Image Logs
Authors: Al Ibrahim Mustafa A , Torlov Vladislav , Mezghani Mokhles M
Published: September 2021

Sidewall coring is a cost-effective process to complement conventional fullbore coring. Because sidewall cores target exact depth points, verification of the sidewall core recovery depth is required. We present an automated, fast workflow to perform the depth verification using borehole images, thereby providing consistent results. An application example using a typical dataset is used to showcase the workflow. A novel automated approach based on image analysis techniques and Bayesian statistical analysis is developed to verify sidewall core recovery depth using borehole image logs. A complete workflow is presented covering: 1) utilization of reference logs, e.g., gamma ray, to correct image log depth using cross correlation and/or dynamic time warping, 2) automated identification of sidewall core cavity in borehole image log using the circle Hough transform, and 3) estimation of confidence in the identification using Bayesian statistics and specialized metrics. The workflow is applied on a typical dataset containing tens of sidewall core cavities with varying quality. Results are comparable to the manual interpretation from an experienced engineer. A number of observations are made. First, the use of reference logs to correct the image log allows for determining the exact well logs values where the sidewall core was sampled, which is then compared to the initial target well logs values. This increases the confidence that the target lithofacies was sampled as planned. Second, the circle Hough Transform is suitable for this problem because it provides stable solutions for partially imaged sidewall core cavities typical in pad-based borehole images. Third, the use of Bayesian statistics and specialized metrics for the problem, such as average and standard deviation borehole image intensity in the cavity, provides customizability to work with multiple types of borehole images and with varying initial depth guess uncertainties. Overall, the use of fast and automated methodology for depth verification opens up avenues for near real-time combined sidewall coring, imaging, and verification workflows. The novelty in this study lies in using a combination of image processing techniques and statistical analysis to automate an established manual workflow. The automated workflow provides consistent results in minutes rather than hours. Results also incorporate a confidence index estimation.
Mangala Polymer Flood Performance: Connecting the Dots Through in Situ Polymer Sampling
Authors: Shankar Vivek , Sunit Shekhar , Brown Alasdair , Kumar Gupta Abhishek
Published: September 2021

The paper describes the in-situ polymer sampling in Mangala which helped explain the performance of a large polymer flood in Mangala field in India.

The Mangala field contains medium-gravity viscous crude oil. Notably, it is the largest polymer flood in India and 34% of the STOIIP has been produced in 11 years of production. Mangala was put on full field polymer flood in 2015, six years after the start of field production on water flood in 2009. Polymer flood added 93 million barrels above the anticipated water flood recovery in 6 years. Reservoir simulation models could replicate the initial Mangala polymer flood performance. However, the performance of the lower layers of Mangala (FM-3 and FM-4) continued to progressively deviate from modeling estimates. Equally importantly, the prediction of polymer breakthrough deviated significantly from modeling estimates.

After 6 years and 0.7 pore volumes of polymer injection, it is apparent that field performance is equivalent to only 50-60% of the viscosity of the polymer injected at the surface. To better understand and quantify the nature and extent of polymer degradation it is necessary to gather representative down hole samples of polymer which has stayed in the reservoir conditions for a considerable length of time. Accelerated ageing studies in the lab showed HPAM can lose viscosity and precipitate after prolonged exposure to Mangala reservoir conditions with an increase in the degree of hydrolysis as the primary reason for the degradation. The concept of transfer function based on first order kinetics was used to extrapolate the laboratory results to Mangala reservoir temperatures. To test the hypothesis, a multi-disciplinary team implemented a plan to gather a representative polymer sample from the reservoir. The polymer sample had been in the reservoir for nearly 120 days and was captured in low shear and anaerobic conditions to minimize shear and oxidative degradation.

The sample was tested for degree of hydrolysis by NMR method. The results confirmed that the level of hydrolysis of the injected HPAM did increase in the reservoir leading to lower viscosity and reduced lower amide concentration. Preliminary simulation studies using the concept of viscosity half-life were used to mimic the polymer degradation with time in the reservoir. The method is quite a simplistic representation of the thermal degradation, but it significantly improved the model's water cut predictions for lower layers and the full field polymer breakthrough predictions. The impact of polymer precipitation in the reservoir on the permeability is under study and it will drive the next phase of more detailed modeling.
A Predictive Model to Detect the Impending Electric Submersible Pump Trips and Failures
Authors: Peng Long , Han Guoqing , Pagou Arnold Landjobo , Zhu Liying , Ma He , Wu Jiayi , Chai Xiaolong
Published: September 2021

Trips and failures are common occurrences in the Electric Submersible Pump (ESP) systems. The random nature of these trips and failures will lead to low industry run-life and high workover costs for ESP companies and operators. To perform early detection and take corrective actions to handle the potential incidents, ESP operation data collected from downhole and surface sensors are used to perform diagnostics and prognostics to identify trips and failures. In this study, Principal Component Analysis (PCA) method serves as a pre-processing method to retain the most essential principal components to reevaluate the initial ESP system. For a single well system, the Squared Prediction Error (SPE) and Hotelling T-square statistic (T2) equations are employed for numerical visualization in the new principal component space and therefore detection of the potential ESP trips or failures. For the whole well group, the score plot of three principal components provides a solution that enables to distinguish different clusters of stable operation, trip and failure regions, and diagnose the upcoming ESP trips and failures. In this way, the predictive model is bulit to continuously analyze the ESP operation and automatically perform health monitoring for any ESP system. This paper concludes that the predictive model has the potential to construct a real-time proactive surveillance system to identify dynamic anomalies and therefore predict developing trips or failures in the ESP system.
Is Decline Curve Analysis the Right Tool for Production Forecasting in Unconventional Reservoirs?
Authors: Molina Oscar , Santos Laura , Herrero Francisco , Monaco Agustin , Schultz Darren
Published: September 2021

This study presents a novel metaheuristic algorithm that uses a physics-based model for multi-fractured horizontal wells (MFHW) to accurately predict the estimated ultimate recovery (EUR) for unconventional reservoirs. The metaheuristic algorithm creates a sizeable number of stochastic simulations and keeps the simulation results from those random models that closely reproduce observed production data. Unlike other optimization methods, the proposed algorithm does not aim at finding the exact solution to the problem but a group of sufficiently accurate solutions that help to construct the partial solution to the optimization problem as a function of production history.

Results from this work provide sufficient evidence as to why traditional decline curve analysis (DCA) is not a suitable solution for production forecasting in unconventional reservoirs. Two case studies are discussed in this work where results from both modeling strategies are compared. Evolutionary prediction of EUR over time using DCA behaves erratically, regardless of the amount of historical production data available to the regression model. Such erratic behavior can, in turn, yield an erroneous estimation of key economic performance indicators of an asset. In contrast, the proposed metaheuristic algorithm delivers precise and accurate results consistently, achieving a significant reduction of uncertainties as more production data becomes available. In conclusion, the proposed partial optimization approach enables the accurate calculation of important metrics for unconventional reservoirs, including production forecasting and expected productive life of an asset.
Understanding AICD Gravel Packing
Authors: Pedroso Carlos , Govinathan Kesavan , Mickelburgh Ian , Wassouf Philip , Latini Carolina
Published: September 2021

In recent years, it has become common practice for operating companies to make a significant effort in the planning of gravel pack installations, especially in their most important wells. Typically, the placement of the gravel pack is accurately modelled, and multiple contingencies developed for potential alternative scenarios to reduce the overall risk of execution. After the pack has been placed, the use of down-hole gauge data enables the gravel pack to be fully evaluated in order to confirm success and investigate any issues or failures. This understanding feeds into improved designs and ever higher success rates for future completions.

The most challenging gravel packs Operators are installing today are those placed in long horizontal open holes, around screens fitted with Inflow Control Devices (ICDs) or Autonomous Inflow Control Devices (AICDs). Simulating gravel pack placement in wells such as these requires the effective modelling of unusually dynamic and complex flow paths. Until recently, no simulator could adequately model these treatments. Most jobs have also been done without the downhole gauges necessary for a complete job evaluation, which has resulted in a lack of data for job evaluation and understanding.

Consequently, completions requiring the pack to be placed around ICD/AICD screen assemblies have, until recently, been done without the assurance of pre-job gravel pack placement modelling. The lack of an adequate simulator has also meant that, even on these complex and valuable wells, Operators have been restricted to simple volumetric evaluation of their success. With no way to understand actual packing mechanisms or investigate root causes of failures, the assumptions made on how packing occurs in these complex wells have remained unconfirmed.

Recent evolution of gravel pack simulators has made the effective pre-job simulation, and post-job evaluation, of gravel packs placed around ICD/AICDs a reality. This paper presents the results of the first evaluation of a multi-proppant deep water horizontal alpha beta gravel pack around AICD screens. It facilitates the understanding of how such gravel packs are placed, validates the packing efficiencies, and illustrates the benefits of using multiple gravels for packing.
Assessment of Radius of Investigation of Pressure Transient Analysis in Highly Heterogeneous Reservoirs
Authors: Zeybek Murat , Jiang Lei , Dumont Hadrien
Published: September 2021

The radius of investigation (ROI) of pressure transient analyses has been traditionally assessed using analytical formulations with basic reservoir parameters for homogenous systems. Numerous studies aimed to improve ROI formulations to incorporate all reservoir and testing parameters such as gauge resolution and rate for more accurate ROI assessments. However, new generation wireline formation testers aim to improve deep transient tests with significant developments in gauge resolution and increasing rate. Challenges still remain in heterogeneous formations such as shaly sands and carbonate reservoirs.

In this study, detailed conceptual high-resolution numerical models are set up, including comprehensive reservoir and measurement parameters, to investigate more realistic ROI assessments in layered heterogeneous systems without and with hydraulic communication. Several conceptual examples are presented in layered systems with permeability contrasts.

In addition, deviation from infinite-acting radial flow (IAFR) and pressure propagation in highly heterogeneous layered systems are investigated to detect the presence of geological features, including closed boundary systems and the presence of a fault in the proximity of wellbore.