bluuebunny/crossref_metadata_2025 huggingface dataset:
Collaborating in the Metaverse for Successful Subsurface Reservoir Characterization
Authors: Norlund Philip , David D'Angelo
Published: March 2023

With increased pressure on energy companies to reduce costs whilst also planning more complex wells with lower carbon emissions, companies worldwide are always looking for ways to be more efficient & successful in their subsurface reservoir characterization. Improved collaboration across the traditional gaps in the Exploration & Production (E&P) disciplines is an important way to achieve these goals. In this paper, we review the vision of the Metaverse, a fully realized digital world that exists beyond the one in which we live and continues to exist even when we do not interact with it. The Metaverse has some key technological concepts that potentially provide a roadmap to help deliver desired improvements for reservoir characterization collaboration. The first is through an immersive three-dimensional world that can bring together people from remote locations to collaborate in one space. The second is through the realization of a Subsurface Digital Twin. We review where we are and what can be achieved with current technologies using our own research and development as examples, and we postulate on how these technologies will be improved in the immediate future.
Small Scale Projects Planning Best Practices in the Oil and Gas Sector
Authors: Al-Hawas Ahmed I. , Al-Harbi Fahad S. , Amminudin Kamarul A.
Published: March 2023

The intent of this paper is to share the Root Cause Analysis (RCA) that is addressing the small-scale project performance issues, focusing on project schedule and milestone deliverable completion delays. Moreover, investigative data analysis was performed for similar previously completed industrial projects, revealing delay causes and different aspects of project performance issues, including scope creep, quality, stakeholder's management and communication gaps. Finally, the corrective action plan is put in place to ensure continuous project performance improvement, by closing all gaps throughout project life cycle phases. The methodology developed in this paper takes into consideration the various types and nature of small industrial projects with budget ranges from $20,000 to $4,000,000, and a two-year execution time frame. The methodology involved data gathering from 36 previously completed projects, as well as interviews with key stakeholders. Moreover, it included Ishikawa "Fishbone" diagram and a gap analysis model to deep dive into the root causes and gap analysis. Finally, a road map addressing the required recommendations was formulated to ensure excellence in project management execution.

Disclaimer: The content of this article represents the author's point of view not the company.
NGL Operation Strategy Using Predictive Analytics
Authors: Qurashi Abdulaziz
Published: March 2023

Oil & Gas is a data-rich industry which is prime for data-driven and decision making. The significant growth witnessed in the digital transformation field and the new era of the industrial revolution 4 (IR 4.0), is a direct result of the need within the industry to utilize the large amount of data to make better decisions, improve operation strategy, plan better for preventive maintenance (PM), and process improvement.

The uncertainty associated with estimating the incoming feed gas rate to NGL plants has resulted in deviation from optimal compressor recycle rate, missed opportunities of meeting planned PM and imposed urgency during operation. Utilizing machine learning algorithms, namely regression and decision tree model, the incoming feed gas can be predicted which result in the machine learning algorithms which results in the identification of the optimum number of running trains and recycle rate required for efficient operation.

NGL-Operation Planner (NGL-OP) is the outcome of utilizing ML algorithms which provides the ability of predicting incoming feed gas, identifying optimum number of running trains required as well as estimating the optimal recycle rate. Adopting this approach is a new and strategical way to plan NGL operation. The developed tool also has the ability to advise whether to shut down, maintain existing operation or starting-up a new train.

The implementation of the model resulted in a significant improvement in NGL operation. The improvement includes fuel gas consumption reduction of around 449 MMSCF/Year which resulted in a significant cost saving, reduction in emissions around 27 M tons/year, and 10% reduction in operating unnecessary running trains. These savings have been achieved through the utilization of the NGL-OP to minimize uncertainty and improve our planning strategy.
Successful Accelerated Reduction of CO2 Emissions through a Statistical Approach
Authors: Al Salmi Ahmed , Al Balushi Sara , Al Zaabi Yousuf
Published: March 2023

Power consumption is one of the leading producers of Greenhouse Gases and improving it will support Petroleum Development Oman (PDO) to meet its target of net-zero emissions. In 2020, PDO operations emitted tons of CO2 with the highest quantity coming from X field where High Voltage pumps, which consume about 15MW resulting in 75,000 tons of CO2 emissions per year, are used. This paper will discuss the approach used to investigate and solve the given problem.

The six-Sigma methodology was used to investigate the high-power consumption in water injection and deep-water disposal processes. Pareto analysis, which was used to scope the project, showed that 35% of power consumption is related to High Voltage injection pumps. The historical data of the response (power consumption) and potential causes of the problem were gathered from the field database. Minitab, a statistical data analysis software, was used in this problem investigation in addition to other Six-Sigma methods including process capability, hypothesis testing, and control charts. Graphical and statistical tools were also used to examine the relationship between the response and variables.

Process mapping identified 27 potential causes of higher power consumption in five High Voltage pumps. The historical data of the variables were statistically correlated to measure the strength of the relationship with the response. The analysis concluded that suction pressure for pumps 1510 and 1520 is the statistically significant cause of higher power consumption. The power consumption of these two pumps was directly linked to the suction pressure using the Pearson coefficient factor and p-value. The suction pressure was too low which caused the pumps to consume more energy to pressurize water. Hypothesis testing resulted in a p-value of 0.00, confirming a strong relationship between power consumption and suction pressure. Appropriate countermeasures were developed, and a new pump operation philosophy was implemented, whereby one pump is always kept on standby. This resulted in a 4MW reduction in power consumption and, ultimately, prevented the emission of 18,000 tons of CO2 annually. Other benefits to date include a saving of around $2.6 million per year, with the potential to save more through replication. Additional yet unquantified benefits include curbing the impacts of climate change on the environment.

The Six Sigma statistical approach is used to understand the hidden causes of the increase in power consumption that result in higher CO2 emissions. The reduction of power consumption in PDO's X field has paved the way for 10 other projects in the Company to reduce their CO2 emissions. We can partner with other operators in the Sultanate of Oman to follow Petroleum Development Oman's example of using the Six Sigma approach in Energy Transition.
Geological Risks and Resources-Based Portfolio Ranking and Completion Optimization by Areas: An Eagle Ford Case Study
Authors: Hong Sahyun , Fataierge Ahmed , Zahrani Abdulkarim
Published: March 2023

Asset ranking plays a critical role for the business success. Given the risk and value of asset, choosing an asset by the highest expected value is not guaranteed to be the best decision because it does not consider the uncertainty in the expected value and decision maker's changing tendency toward the risk. The first part of this paper presents an application of the modern portfolio theory to the Eagle Ford unconventional resources and shows how the assets can be prioritized by taking into account the subsurface-based expected value and the uncertainty. For the fair comparison of the asset's potential, the influence of completion parameters is excluded in the asset ranking. With the stationary completion designs across the assets, the asset is evaluated and ranked only by the subsurface quality. Having the selected asset area, the second part of this paper focuses on optimizing the completion designs. Well production trend is predicted against the varying completion designs over the selected asset area and displayed onto the axes of the completion parameters of interest. Optimizing over the selected asset makes a smaller number of data available. Some completion parameters may be fixed due to operational issues – e.g. limited range of porosity and reservoir pressure in a selected asset, with the limited lateral length and total proppant amount. A data-analytics approach with a data simulation technique has been developed. Tens of thousands additional data for the input variables (subsurface and completion) is generated by a data simulation technique. These simulation data are inputted to the statistical predictive model built for the well performance so that many data points for completion, subsurface and well performance are available. With the help of simulation data, any well performance trend analysis with key completion variables of interest with some constraints for other variables is possible.
Understanding Lateral Permeability Variations Using Integrated Logging-While-Drilling Azimuthally Oriented Formation Testing and High-Resolution Imaging in Heterogeneous Carbonate Reservoirs
Authors: Kumar Ashok , Fateh Ahmed , Taher Ahmed , Fouda Mohamed
Published: March 2023

Permeability is a fundamental petrophysical attribute required to accurately evaluate recoverable reserves and design an appropriate field-development strategy. Because logging tools do not measure absolute permeability, minimizing uncertainty in the evaluation of log-derived permeabilities remains one of the most critical petrophysical challenges in the oil industry. Horizontal development in laterally heterogeneous carbonate reservoirs also requires evaluation of lateral permeability variations to optimize completion design, while maximizing reservoir exposure via precise well placement in real time. This paper demonstrates innovative methods to evaluate lateral permeability variations in heterogenous carbonate reservoirs.

The workflow for log-derived permeability predictions is based on empirical relationships using nuclear magnetic resonance (NMR), acoustic, and high-resolution imaging tool measurements. These are normalized in an integrated multi-disciplinary approach using core, well test, production logs, and formation-tester mobility data where available. Traditionally, formation-tester tools have been used to obtain single pressure and mobility values at each test station. The logging-while-drilling (LWD) formation tester can be oriented azimuthally to help evaluate permeability anisotropy, which is a key factor for reservoir characterization in laterally heterogeneous reservoir layers. The oriented data can also be used to adjust the well plan in real time to maximize reservoir exposure in the desired "sweet spot."

Variations in the oriented LWD formation tester measurements at each depth station exhibited favorable correlations to azimuthal changes observed in the LWD high-resolution micro resistivity image. Detailed image analysis further helped to understand the mechanism that governs the azimuthal permeability profile. The combination of oriented LWD formation-tester and high-resolution image data also aided in making better real-time geosteering decisions, as well as in the planning and design of a future field-development program within the local reservoir sector. Operational considerations to maximize data quality rely on an optimized bottomhole assembly (BHA) design, accurate depth control, and robust orientation techniques based on best practices and lessons learned.

This paper presents an integrated approach for well placement and an improved understanding of flow-unit characterization via first-time use of oriented formation-tester data in conjunction with corresponding high-resolution images in a laterally heterogeneous reservoir.
Shale and Carbonate Wellbore Stability Charts for Drilling Operations
Authors: Al Ajmi Ahmed , Shaheed Bilal , Al Ajmi Adel , Al-Hadrami Hamoud , Al-Aamri Mohammed
Published: March 2023

The oil industry suffered a great deal of time and financial damage because of wellbore instability problems reflected by well collapsing. This suggests that more meticulous well drilling planning are required to avoid such rock failure. Shale has been a difficulty for many drilling operators, and shale instability difficulties are to blame for 90% of borehole collapse problems. Additionally, compared to shale or sandstone, carbonate rocks are believed to be more capable and to face less instability problems. However, carbonate-based reservoirs make up the majority of the world's hydrocarbon reserves. As a result, a sizable number of wells are drilled in carbonate deposits every year. Due to this, there are now more wellbore instability problems being experienced while drilling carbonate formations globally.

Rock failure will occur if the field's rock mass is subjected to a huge stress beyond what it can withstand. Construction of models that can foresee the conditions in which a rock can fail will greatly aid in preventing serious problems like borehole collapse and solids generation. Therefore, by accurate geomechanical modeling, the most suitable mud density and borehole trajectory should be understood in advance before drilling. The Mogi-Coulomb failure criterion and a linear elastic stress model for the field are utilized in this study as a geomechanical stability model. The effects of all the major stresses in the fields are reflected and depicted in this three-dimensional stability model. For the benefit of all drilling engineers and operators in Oman, various charts are produced using the stability model.

Wellbore stability study is generally a difficult task that may need for a highly specialist consultation and is a time-consuming procedure. An important requirement that is overlooked in the oil and gas sector is the need to simplify the wellbore stability analysis in a way that makes it simple and ready for direct use by drilling engineers. The stability charts give the minimum allowable mud density for shale and carbonate rocks to prevent borehole collapse for all drill trajectories. Due to the emphasis on Oman's shale and carbonate formations and the most common possibilities, the created charts are limited for ranges of rock geomechanical characteristics. According to the input parameters, the produced stability charts are divided into several groups. The effect of each geomechanical property is studied to understand the relationships among them. The produced charts for shale and carbonate deposits in Oman and elsewhere are used in actual field case studies. Some of these field applications have already been carried out, while others are still in the works and will likely be discussed in a future project.
Identifying and Ranking Multiple Source Models for Transfer Learning in Unconventional Reservoirs.
Authors: Cornelio Jodel , Mohd Razak Syamil , Cho Young , Liu Hui-Hai , Vaidya Ravimadhav , Jafarpour Behnam
Published: March 2023

When a limited number of wells are drilled at the early stages of developing unconventional fields, the available data is insufficient for developing data-driven models. To compensate for the lack of data in new fields, transfer learning may be adopted by using a previously learned model/knowledge from similar fields (source data) to build a predictive model for the new field. To be effective, transfer learning requires the source and target fields to have similarities and to ensure relevant information/knowledge is transferred. The transfer of irrelevant knowledge may impede the training process and lead to a negative knowledge transfer. When multiple source data are available, it is important to identify each source data's relevance and potential contribution to the target data. We introduce a framework to rank different source datasets and determine their capability for transfer learning. The methodology relies on using knowledge learned from datasets with similar features to the target dataset. This methodology helps circumvent the data needs for training while ascertaining that the right knowledge is transferred when developing new fields. Additionally, the framework allows for combining relevant features from multiple source models (with similar ranks). It allows for transferring the knowledge learned from mature fields to improve the performance of deep learning proxy models for new fields with similar features.
Sustainable Energy for Rotating Equipment: Train Driver Technology Selection and Lifecycle Impact Assessment
Authors: Abu Sanah Hassan , Goretzki Peter
Published: March 2023

In line with sustainable energy utilization and global decarbonization effort to reach net-zero emission targets, a closer look to variable speed Electrical Drives (ED) as system for Rotating Equipment (RE) is investigated to assess the impact of drive selection towards achieving higher operational excellence in conjunction with end-user and plant operator operation excellence targets. The paper briefly introduces main available variable speed ED systems with relevant attributes for holistic Total Cost of Ownership (TCO) assessment approach that can be streamlined for any RE application in energy industries with pre- defined application-specific boundary conditions.

Paper focuses on RE asset such as centrifugal gas compressors and pumps driven by means of Electric Motor (EM) in oil and gas, petrochemicals, and energy industry. Holistic TCO approach covers practical methodology of impact calculation for ED systems. Namely Mechanical Variable Speed Drive (MVSD), Electro-Mechanical Drive (EMD), or Variable Frequency Drive (VFD) system technologies. Established valuable insight from system-wise TCO assessment provides decision makers with reliable feasibility and data-driven conclusion measure to select most sustainable system for RE operation with variable speed over desired lifetime cycle as TCO holistic approach covers ED systems CAPEX and OPEX respectively.

System TCO approach is further presented as deployed on real project assessment in Middle East for a compressor drive running at 10,900 kW rated power and 10,000 rpm. With Holistic TCO assessment including commercial and ecosystem requirements, EMD and MVSD solutions respectively demonstrated higher success measures as sustainable ED solutions over compressor train lifecycle. Benefits for each ED technology is briefly discussed with its relevant carbon footprint saving potential through equivalent CO2 emissions from consumed energy. Finally, brief highlight on recent successful project deployment of MVSD technology is presented for compressor drive in bio-fuel application as adaptability potential to current market agile shift in sustainable energy sources and various application operability requirements demand.
Optimizing the Hydraulic Fracturing Fluid Systems Using the Completion and Production Data in Bakken Shale
Authors: Alotaibi Najd , Dursun Serkan
Published: March 2023

Objectives/Scope. Well completion is an important step for every well to undergo in order to prepare it for oil and gas extraction. Based on the nature and characteristics of an oil and gas reservoir, appropriate well completion practices are selected to enhance the production. Hydraulic fracturing is one such technique. It frequently involves horizontal drilling and injecting fluids under high pressure to fracture the rock. The larger fractures along with the injected fluid enable high amounts of trapped natural gas and crude oil to flow out of the formation to the producing well bore. In well completion, a variety of chemicals are employed to leverage oil production, and the goal of this study is to determine how such chemicals impact performance rate in several unconventional wells in the Bakken Shale.

Methods, Procedures, Process. In this approach, two Completion and Production datasets from North Dakota (the Bakken Shale) and fracFocus were processed and combined accordingly which resulted in some of the following parameters, type of chemical and amount of chemical, and true vertical depth of the wells. And the dataset that was produced was analyzed based on the stimulation treatment. The proposed workflow utilizes supervised machine learning algorithms to train different predictive models to estimate the amount of the produced oil; including but not limited to neural Random Forest, CATboost and XGboost. Additionally, by quantifying each chemicals’ importance on oil production, this investigation was able to determine each chemical's influence.

Results, Observations, Conclusions. This study examined the impact of more than 2500 different completion chemicals on the oil production of unconventional reservoir and discovered the chemicals with the highest significance on the oil production, given that, the predictive models were able to estimate the oil production accurately after feeding it with the type and measures of the most influencing chemicals.

Novel/Additive Information. The most important pillar of this framework is that it expedites the workflow of hydraulic fracturing jobs in the unconventional reservoir by providing an accurate model that optimizes its parameters to maximize the oil production rate. This solution offers an automated decision-making process for the selection of chemical types to be used in the hydraulic fracking jobs. The choice of chemicals in fracturing fluids is affected by many variables, including its compatibility with the target rock formation to be hydraulically fractured, the geology of the rock formations being drilled through, the pressure and temperature measurements in the target formation, cost, operator preference, and possible interactions between chemicals in the treatment fluid.
Well Design Re-Engineering: First Level of Emission Footprint Optimization
Authors: Nifantov Aleksandr , Ruzhnikov Alexey
Published: March 2023

Well construction is one of the greenhouse gas (GHG) emissions contributors in the oil and gas industry. Today, the main attention is paid to technology solutions, minimizing drilling time and rig upgrading with low-energy equipment. However, what about optimum well design itself, which may lead to acceptable operational risks, reasonable budget, lower power demand and consequently lower emissions to deliver it? The work presented in this paper is about the planning process to reach not just a technical and financial balance in the construction of a well, but also incorporate sustainability elements into the design process itself.

The conventional engineering approach to designing a well, namely being able to meet its technical targets within reasonable budget, was upgraded with an additional workflow to consider the GHG emission footprint of well construction process. Specifically, it was incorporated in a digital solution which enables a comparison between different well program scenarios, from which an optimal design can be chosen. The process includes the following step: 1) creation of a well design meeting its technical targets; 2) estimation of the well budget; 3) modeling the well construction GHG emissions for the different designs. Some iterations of this process are needed to reach sustainable well design (relatively optimal case).

The real extended reach drilling (ERD) well proposal was used as the example for this study. The 3D geomechanical model was created prior to start the well engineering. It simulated distribution of stresses which enabled calculation of the safe pressure window while drilling, tripping, running casing and cementing. Considering this model, the originally proposed casing design was upscaled to achieve the ECD (Equivalent Circulating Density) in the required range without collapsing and breaking down the wellbore wall. Additionally, the trajectory was optimized to improve hole cleaning and facilitate the running of casing in highly deviated sections of the well. All these measures theoretically minimized the risk of not hitting the planned targets. Then, the well profile was tuned to improve the financial impact and operational emission footprint without compromising technical solution. As a result, it had led to potential lowering of the well construction budget by ~2 % and reduction of the emission by 6.3 % (for the sum of Scope 1 and 3 emissions).

The main idea of this approach is to achieve a low-energy, cost-effective and technically feasible well design as a baseline. Within the constraints of this design, it will then leverage specific technology solutions to further minimize energy consumption and GHG emissions.

This manuscript presents a new methodology for the engineering design process for oil and gas wells, which quantitively incorporates sustainability. The ideas, which are expressed in the manuscript, can be implemented in any drilling project worldwide.
Smart Algorithms for Determination of Interfacial Tension (IFT) between Injected Gas and Crude Oil – Applicable to EOR Projects
Authors: Kalam Shams , Khan Mohammad Rasheed , Shakeel Muzammil , Mahmoud Mohamed , A. Abu-khamsin Sidqi
Published: March 2023

Rampant move towards the energy transition landscape has propelled the need to reduce and manage greenhouse gas (GHG) emissions. To this end, it is pivotal to explore cost-effective avenues to utilize GHG and flue gases that can lead to achieving a reduction in emissions target and provide EOR opportunities. Accordingly, the injection of these gases in oil reservoirs allows for hitting two targets with one arrow. Nevertheless, the success of these projects is dependent on accurate IFT estimates between injected gas and resident hydrocarbons. Therefore, this paper evaluates the utility of machine learning algorithms for the estimation of IFT between a mixture of CO2:N2 and straight-chain alkanes for variable temperature/pressure conditions.

A systematic approach is adopted to implement predictive models for IFT prediction by utilizing over 250 experimental data points from the available literature. A comprehensive statistical analysis is performed to achieve model generalization capabilities and improve control over the most relevant input parameters. Consequently, IFT is demarcated as a function of four readily available inputs with pressure and temperature being the most obvious, while carbon number and flue gas mole fraction is also incorporated as critical parameters. Various smart approaches in this work are proposed through the development of an IFT predictor using Artificial Neural Network (ANN), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost) algorithms. Machine learning model training is enhanced using a K-fold cross-validation technique combined with the exhaustive grid search algorithm. Post-training, the developed models are tested for reliability using blind datasets reserved for this purpose.

A fair comparison between model efficiency is ensured by using an in-depth error analysis schema that includes various metrics like the correlation of determination, average error analysis, graphical error analysis, and scatter plots. This allows a relative ranking system to be generated that weighs various factors to classify one model as the most efficient. For the IFT prediction problem, it was found that the neural network was aptly able to yield high efficiency and low errors. This stems from the way ANNs function to map the non-linearity relationship between carbon number and the IFT. It was also observed that enhancement of the intelligent model training through multiple techniques resulted in optimized hyperparameters/parameters.
Iterative Integrated Planning and Scheduling Model in Project Management
Authors: Bopalia Vinod Savji
Published: March 2023

Quite often, project planning and scheduling are used interchangeably but they have different roles in the successful completion of a project. On a higher level, the project plan is the master blueprint which drives the project towards achieving objectives while the project schedule details the specific tasks to be executed by individual or set of groups to achieve project's goal.

Project planning primarily involves selecting the appropriate procedures and methodologies required to deliver the project on time. Project scheduling, on the other hand, converts the defined plans, scope, and cost into an operational timeline with specific set of objectives within allocated budget. Main factors in planning and scheduling those differentiate these two phases in the project management specified in the below table. FactorsPlanningSchedulingDeals withWhat and HowWhen and WhoDefinitionPlanning is process of developing a tool to design and produce the desired unique deliverables.Scheduling is the process that defined the time frame in which the project's deliverables will be accomplished and the sequence of tasks.Focus onOverall project objectives and business value creation.Assign various sets of tasks to the available resources for a specified time duration.ImpactFrom beginning until end of the project.During project execution and closure.

Some organizations integrate the jobs and functions of planning and scheduling in a single position. There are benefits to this approach because a project scheduler can't fully understand the nitty gritty when it's time to have resources on the floor without also having firsthand information about the project's entire scope in place. This approach gives remarkable results when the project is small to medium with less engineering disciplines involved. However, for the medium to large scape project will require dedicated functions of planning and scheduling independently.
3D Printed Rocks - An Emerging Technology for Systematic Petrophysical Studies
Authors: Ma Shouxiang , Jin Guodong , Antle Ryan , Wieneke Brian
Published: March 2023

3D printing translates digital models into physical objects, which could potentially be used to print proxies of reservoir rocks from their high-resolution images acquired by such as micro-CT tomography. This paper reviews current 3D printing technologies and explores the capabilities of 3D stereolithography (SLA) technique in rock printing in terms of scale, resolution, accuracy, and repeatability, with the eventual objective of studying factors affecting petrophysical models, such as Archie model, by varying petrophysical inputs of Archie parameters m and n, systematically.

A 3D printer with the resolution of 10 μm is used to print rock models. Two types of digital models are designed for the 3D printing: Model I contains straight cylindrical pores; 19 pores with diameters from 10 to 100 μm with an increment of 5 μm, and Model II is a virtual core of 1 inch diameter and 2 inch length, created from a computer-generated random uniform sphere pack with a porosity of 30%.

Model I cylindrical pores of down to 10 μm are printed and clearly observed on their micro-CT images. Pore connectivity is well preserved in the print proxy. However, the printed pore shapes are not completely circular as designed, indicating a challenge of shape preserving in printing. Pore sizes vary along the axis with a standard deviation of approximately 2-3 μm. In Model II virtual core printing, high printing accuracy and repeatability are achieved, while issues of converting from the digital design model to printer recognized STL model are discovered and being resolved.

With continuous advancements in high resolution imaging, digitalization, and computing power, 3D printing could become a unique and innovative approach enabling manufacturing multiple rock samples for repeatable experiments with identical samples, experiments with systematic variables of such as pore structure or wettability. Challenges faced for printing full-scale pore-structure driven samples can leverage future development and applications of the evolving 3D printing technology.
Assessment of Condensate Banking Growth Using Advanced Pressure Transient Analysis
Authors: Al Khamees Ali , Phillips Guerrero Rodolfo , Alodah Meshari
Published: March 2023

Condensate banking is a process that occurs in gas wells when the reservoir pressure goes below the dew point. The depletion process introduces an additional fluid complexity, which complicates reservoir dynamics and reduces ultimate recovery. In addition, it hinders well performance and productivity due to its growth over production time.

Estimating the current extent of condensate banking and predicting its progression over time plays a major role in optimizing well performance. Using single-phase pressure transient analysis to account for different mobility regions is widely practiced across the industry. However, a non-linear model must be utilized for the conditions where more than one phase exists, such as in gas condensate reservoirs. The model should consider non-linearities such as relative permeability curves for multi-phase systems, and pressure-dependent PVT properties such as viscosity, condensate gas ratio, and fluid compressibility.

Non-linear modeling provides an accurate estimation of the different characteristic regions caused by condensate banking in terms of distance, mobility, and saturation variations, ensuring proper reservoir characterization. Additionally, with the utilization of test design function, non-linear modeling predicts condensate banking development, giving a precious indication of future well and reservoir conditions. The deployment of the advanced non-linear model in the pressure transient analysis (PTA) results in reasonable estimations of condensate banking distance from these wells. Finally, the results of the non-linear method highlighted the difference when compared to single-phase models, showcasing the importance of mimicking actual well and reservoir multi-phase conditions properly.

In this study, we will illustrate pressure transient analysis test designs in condensate reservoirs, highlighting the condensate banking effect on the well performance and the extent estimation of the fluid bank utilizing a non-linear modeling approach as an aid in optimizing well performance.
Critically Stressed Faults and Fractures Analysis
Authors: Alhasan Abdullah , Qahtani Yahya
Published: March 2023

Critical stress analysis is one of the approaches for assessing reservoir quality, and it enhances understanding of the seal capacity and migration pathways in a petroleum system. It also helps identify fractures with high and low conductivity. This analysis assesses the effect of principal stresses to reveal faults that are critically stressed and stable.

Faults were interpreted manually using seismic and other volumetric attributes such as the variance and the ant-track. Principal stresses and fault stress parameters were extracted from mechanical earth models in the area. These faults, along with the principal stresses, were then used as input for a fault stress analysis tool to measure how stressed the faults are. The analysis incorporated depth dependence as the overburden was one of the main parameters affecting the outcome of the study. Finally, the results of the study were calibrated using real-time data such as drilling events from several wells drilled in the area.

With increasing depth, the additional pressure needed for faults and fractures to reach failure increases accordingly. This is expected when considering the overburden effect. Thus, this analysis is considered highly dependent on depth. The shallowest formation showed the highest number of critically stressed faults, while other formations have lower numbers as the depth is increased until there is an insignificant number of stressed faults in the deep formations. In the shallow formations, moreover, the required pressure to fail is insignificant as the overburden stress is low. Furthermore, faults and fractures were expected to require substantial pressure to be critically stressed in the deep formations, and are observed to be considerably stable. Another important factor was the maximum horizontal stress. On the one hand, it helps keep faults open if they are parallel to it, and thus they require substantially less pressure to be conductive. On the other hand, it acts to close those that are perpendicular to it making them much more stable. Thus, the amount of pressure the fault needs to be critically stressed is significantly increased. Finally, the results of the critical stress analysis were validated via real-time well data such as drilling reports.

The objective of this project was to assess and understand faults and fractures in terms of their stress state by analyzing the principal stresses acting on them. This would highly assist in understanding the seal capacity and migration pathways. To sum up, this analysis aids the assessment of the reservoir quality.
An Enhanced Synergistic Effect in Surfactant-Polymer Flooding Under High-Temperature and High-Salinity Conditions
Authors: Chen Shaohua , Huang Tianping , Han Ming , AlSofi Abdulkareem
Published: March 2023

Two hydrophobically associating polyacrylamide (HAPAM) polymers were synthesized through free-radical micellar polymerization using different hydrophobic monomers. One polymer product – HAPAM-1 contains a linear alkyl chain, and the other one HAPAM-2 bears an aromatic group which is more compact comparing the alkyl hydrocarbons. The properties of both polymer solutions were investigated in high-salinity water (HSW). The interaction between the polymers and a non-ionic surfactant – dodecyl glucopyranoside (DDG) was studied in the HSW at 50 °C using formulations composed of 2 g/L polymer and a series of DDG concentrations. The polymer solutions exhibited a Newtonian plateau at lower shear rates followed by a significant shear-thinning region at higher shear rates. HAPAM-1 exhibited a more pronounced shear-thinning effect than HAPAM-2 due to more rigid hydrophobic junctions self-assembled by the aromatic groups. Upon addition of DDG, the zero-shear viscosities of polymer solutions were found to peak at 15 mg/L of DDG concentration to both polymer solutions. The interfacial tension (IFT) between oil and water obtained from HAPAM-2/DDG solution was lower than that of the DDG solution without polymer, suggesting a synergistic effect between HAPAM-2 and DDG which further reduced IFT. However, the IFT of DDG solution was not affected in the presence of HAPAM-1. Micromodel experiments indicated that the oil production efficiency by initial HSW injection was quite low, then displacement of residual oil was dramatically improved by injection of HAPAM-1/DDG or HAPAM-2/DDG solution. Extended HSW flooding slightly increased the oil production for both chemical flooding systems. The performance of HAPAM-2/DDG in oil displacement was better than HAPAM-1/DDG, which could be attributed to the higher solution viscosity and lower IFT resulting from more pronounced interaction between HAPAM-2 and DDG. This study aims at probing the effect of different types of hydrophobic units on surfactant-polymer interaction and correlating such interaction with the effectiveness on improving oil production by oil displacement in a porous media.
CO2 Huff-n-Puff: An Experimental and Modeling Approach to Delineate Mass Transfer and Recovery from Shale Cores
Authors: Alahmari Saeed , Raslan Mohammed , Khodaparast Pooya , Gupta Anuj , Duncan Jewel , Althaus Stacey , Jessen Kristian
Published: March 2023

Gas injection has been demonstrated to be an effective approach to enhance recovery from ultra-tight fractured reservoirs where the role of molecular diffusion often becomes dominant. The open literature offers a large collection of work concerned with gas injection studies and projects, employing carbon dioxide (CO2), methane (CH4) and other gases, and reports a considerable improvement in oil recovery over primary production. CO2 injection has an additional advantage over other gases through the potential for geological sequestration. This explains the growing interest in studying diffusive mass transfer during CO2 injection to delineate the sequestration potential in concert with enhanced oil recovery from unconventional resources. However, additional work is needed to arrive at a comprehensive understanding and representation of diffusive mass transfer in ultra-tight fractured formations.

In this paper, we study diffusive mass transfer in shale cores by conducting and simulating CO2 Huff-n-Puff (HnP) experiments at high pressure and temperature. Two cores from a formation in the Middle East were evacuated and then saturated at 3500 psi and 50°C with a synthetic oil consisting of decane (nC10), dodecane (nC12), tetradecane (nC14) and hexadecane (nC16). We performed multiple HnP cycles at varying injection conditions: 2900-4000 psi and 70 °C. Diffusive mass transfer was then investigated via (1) evaluating the effect of injection pressure on oil recovery, (2) analyzing produced oil compositions, and (3) studying the pressure decline during the soaking period.

Our experimental observations show that a higher oil recovery is achieved when injecting at a higher pressure. We also observe that molecular diffusion acts as a dominant recovery mechanism in the HnP experiments, as evident from analyzing the produced oil composition and from examining the pressure behavior versus time during the soaking periods: The observed decline rate in the pressure during soaking signify that molecular diffusion dictates the mass transfer during the HnP experiments. Additionally, we note that miscibility conditions will change from one HnP cycle to another, as the injected gas mixes with an oil composition that changes between cycles.

We have used the CMG-GEM compositional simulator to interpret the HnP experimental results. When multicomponent diffusion coefficients were computed using the correlation of Sigmund (1976) the simulator is unable to provide a reasonable prediction of oil recovery and produced oil compositions. To achieve a better prediction of diffusive mass transfer in ultra-tight fractured reservoirs, a representation that is based on a more fundamental description of the multicomponent diffusion coefficients is hence required, as discussed in-depth by Alahmari and Jessen (2021) and Shi et. al. (2022).
Multidiscipline Well Construction Process Integrates Advanced Engineering Design and MSF Technologies to Deliver Arabian Gulf Trilateral Well
Authors: Adewuya Opeyemi , Alqurashi Mahmoud , Urbina-Arias Rommel , Alodah Faisal
Published: March 2023

The use of multilateral well designs and architectures have progressed significantly since the introduction nearly three decades ago. It has become the de-facto approach for unlocking incremental production performance and increasing drainage density in sands and limestone reservoirs. The tri-lateral well featured in this paper is a TAML Level-2 design with each 6000 ft lateral geosteered and completed by running open-hole packers equipped with ball-activated frac-ports and sleeves on a non-cemented liner hanger system in the motherbore and drop-off systems in laterals-1 and 2. The pre-drill exercise encompassed technical considerations to determine from ---- reservoir type to well architecture, MSF technology, modelling for fracture stimulation effectiveness and well construction techniques --- to ensure success.

Beyond established reservoir development strategies such as Maximum Reservoir Contact (MRC), the robustness and effectiveness of directed stimulation fluid to achieve frac stage deep acid stimulation at design pressures requires open-hole stage isolation technologies and devices that enable confirmation of completion of treatment operation. Additionally, working from bottoms-up, junction construction, debris management, securing well integrity during whipstock installation, window milling and whipstock retrieval are operational phases that pose significant challenge and risk to loss of well.

The collaboration between Multilateral equipment design and engineering companies and Operators focus on simplifying junction construction, High frac pressure Open-hole packers as well as affirmative frac port open and close surface indicators. Innovative engineering solutions has produced advanced open-hole isolation and completion hardware and material science developments are offering path clean-up and unobstructed reservoir fluid flow after stage stimulation.

The integration of the latest multilateral construction technologies and techniques for ensuring mission-critical objectives leverages a multidiscipline collaboration approach to ensure well delivery and reservoir performance. Critical success factors discussed in this paper are, 1. Tri-lateral wellbore construction and recovery of junction construction devices, 2. Running and setting lower completion string, 3. Operating stage isolation devices and effective stimulation of each stage guided by advanced frac-stimulation modelling analysis and 4. Unrestricted reservoir flow through lower completion flow control devices.
Perforation Design and Gun Selection Workflow – A Successful Case History for Deep Penetrating Gun
Authors: Samy Ayman , Gilliat Jim , Khalilov Ruslan , Pashayev Nariman , Mammadov Rufat , Akbarov Akbar , Bahalov Elmar , Allahverdiyev Maarif
Published: March 2023

Perforation design including gun size, type, charge weight, configuration (shot density, entrance hole, phasing) and deployment options can significantly impact well productivity post perforation. Gun selection is a key process to ensure that the optimum gun that can yield maximum well productivity and minimum skin due to perforation has been considered. Gun performance modelling and sensitivity analysis should be conducted to compare the performance of various guns and to select the optimum gun suitable for well and reservoir conditions.

Gun performance under downhole condition is a complex process and uncertainty analysis should be considered when converting API gun test data into downhole condition. It is always preferred to use stressed-core test data such as API section II/IV. However, data analysis and alteration might still be required to replicate the exact downhole condition.

This paper presents a successful case history of perforating 130 m in a single coiled tubing conveyed run using Live Well Deployment system in 6,000-m deep gas and condensate reservoir with an average permeability of 10 mD and reservoir pressure of 12,500 psi. Production has increased by 20% compared to reference wells due to the intensive perforation testing and design process conducted to this well prior to operation.

Extensive modelling work has been conducted to evaluate the performance of deep penetrating guns compared to conventional guns, in addition to uncertainty analysis and risk assessment regarding the impact of using API section-I compared to Section-II/IV data. The paper demonstrates a robust workflow for gun selection and gun performance evaluation process, which can be used as guideline to perforation design process.