bluuebunny/crossref_metadata_2025 huggingface dataset:
Drilled Dry Structures – From Yesterday's Failure to Today's Success
Authors: Das Debasis Priyadarshan , Tiwari Pankaj Kumar , Chidambaram Prasanna , Amir M Syafeeq B E , Tewari Raj Deo , Bt Baharuddin Salina
Published: October 2023

CO2 Storage in deep saline aquifers has potential and small-scale projects have been successful globally while some major projects like Gorgon are in their early phases. Several depleted hydrocarbon fields have been studied in Peninsular Malaysia for potential storage of ~480 to 570 MMscf of CO2 which will be produced daily once high contaminant gas fields will be brought into production. However, due to the limited storage capacity and late availability of such depleted reservoirs, it is necessary to investigate options that might address both storage capacity and timely availability for sequestering the produced CO2. Peninsular Malaysia's deep saline aquifers have the potential not only to address CO2 production in the region, but also to serve as regional CO2 sequestration hubs.

With a holistic approach, a screening matrix was developed to identify the strategic drilled dry structures or saline aquifers. It comprised fault density, presence of top seal(s), reservoir depth, thickness and extension, pressure, temperature, porosity, number of wells drilled & their integrity, and data availability. Structures that met the screening criteria were further analyzed for their CO2 storage capacity based on reservoir pore volume, producible water and CO2 compression factor. They were subsequently ranked based on the evaluated capacities and associated containment & well-integrity risks. Further the feasibility of clustering multiple dry structures (within a ~20km radius) was evaluated for nodal development.

Six potential candidates were discovered from the thirty-four screened drilled dry structures, with individual structures having theoretical storage capacities ranging from 0.5 to 23 Trillion Standard Cubic Feet (Tscf). Two possible clusters were also identified: with Cluster 1, comprising three structures with a potential storage volume range of 1.1 to 1.8 Tscf, and Cluster 2 comprising two structures with a storage capacity ranging between 1.9 to 7.2 Tscf. The study also emphasized the need for more detailed to establish the feasibility of identified storage sites. To date, detailed feasibility studies are being conducted on all these structures to narrow down the range of the storage capacities and to come up with an appraisal plan for additional data acquisition to reduce the uncertainties before these structures are taken up for Storage Development Planning studies.

This is the first-ever screening & evaluation of drilled dry structures/saline aquifers for CO2 storage in the Peninsular Malaysia area. These identified saline aquifers have significant CO2 storage potential that can help unlock the hydrocarbon potential in the high contaminant gas fields in the region on time and cater to the regional CO2 management in Southeast Asia.
Transforming Operations Data into Business Intelligence: Leveraging Natural Language Processing (NLP) and Machine Learning (ML) for Accurate and Sustainable Insights
Authors: Mukherjee S. , Shekhar S. , Martinez S. S. , Gupta A. K. , Kumar S. , Karrar A. Z.
Published: October 2023

Unstructured data constitutes a sizable portion of every organization. When left unattended, it becomes dark redundant data with associated storage costs. This paper introduces a novel approach to information extraction for data management in the oil and gas industry. The data management system (DMS) is a web application that seamlessly integrates structured and unstructured data at the back end, providing actionable insights to users on the front-end. The DMS offers intuitive and interactive features tailored for diverse use cases, including operations planning, sales planning, tender planning, and competition-market share analysis.

The approach consists of two key components: automated extraction and enrichment pipelines, and workflows based on natural language processing (NLP) and machine learning (ML). The automated pipelines efficiently extract, ingest, enrich, and quality-check data from multiple sources. Meanwhile, the NLP workflows focus on unstructured textual data and perform tasks such as named entity recognition (NER), relation extraction, and operation classification to extract relevant information. State-of-the-art language models, such as bidirectional encoder representations from transformers (BERT), are employed to contextualize operational comments and assign labels to the operations.

To evaluate the effectiveness and benefits of the DMS application in addressing various operational challenges, a series of experiments and surveys were conducted, comparing it with existing tools and methods. The results demonstrate that the DMS effectively delivers accurate and relevant information in a user-friendly manner. The key advantage of the DMS lies in its ability to bridge silos between different business lines, enabling stakeholders and users to monitor and analyze data from diverse sources, such as daily drilling reports (DDRs), daily workover reports (DWRs), production, testing, and rigless data.
CO2-Brine Relative Permeability of HPHT High CO2 Complex Carbonate Rocks: Case Study from Sarawak Basin, Offshore East Malaysia
Authors: Kashim M. Z. , Giwelli A. , Clennell M. B. , Esteban L. , Noble R. , Md Shah S. S. , Zaidin M. F. , Tewari R. D.
Published: October 2023

A high carbon dioxide (CO2) carbonate gas reservoirs located in East Malaysia's waters (denoted as S Field) was expected to be developed for hydrocarbons production while storing the CO2 separated from the produced CO2-rich hydrocarbons. High challenge was expected to de-risk the subsurface uncertainties of S Field due to its strong heterogeneity, large amount of CO2 initially present in the reservoir and high reservoir temperature conditions. The permeability of targeted injection is low which makes it more complex in term of characteristics. Relative permeability is one of the most important properties influencing the fate and transport of CO2. Generating relative permeability for CO2-brine in this kind of carbonate rocks system possessed a different challenge due to the CO2 solubility, CO2-mineral reactions and low permeability domain. Thus, this study presents three new sets of relative permeability measurement for drainage conducted in low permeability (<10 mD) carbonate samples which is acquired from targeted injection zone is S Field. Unsteady-state method was employed for the experimental analysis and all the measurements were conducted at reservoir conditions. Mineral packed column was installed to mimic the aquifer brine conditions and eliminate the geochemical reactivity during the tests. Two-phase flow simulator was used to history match the data generated from the coreflooding experiments to generate the representative CO2-brine drainage relative permeability curve. Pre- and post-CO2 flooding core characterization, using RCA (Routine Core Analysis), NMR-T2 (Nuclear Magnetic Resonance) and X-Ray CT-scan were conducted to examine any petrophysical alteration that might take place during the experiment. The results from the three conducted tests showed moderate to high end point relative permeability to CO2 (>0.55) and low to moderate irreducible brine saturation (0.01 to 0.4). Except for the lowest permeability sample, the post-CO2 flooding characterization showed minimal impact in term of petrophysical and micro-structural alterations due to the geochemical inhibition by mineral packed column. The lowest permeability sample was observed to be affected by high injection pressure which altered the properties of the core. Based on the generated relative permeability information, the injection of CO2 into the targeted zone is expected to provide better CO2 flow during CO2 injection and large pore-space capacity for CO2 occupancy which serve as a good candidate for CO2 storage.
Visual Twin for Pipeline Leak Detection
Authors: Hamilton M. , Al-Ammari W. , AbuShanab Y. , Sleiti A. , Hassan R. , Hassan I. , Kaan M.S. , Rezaei-Gomari S. , Rahman M. A.
Published: October 2023

Objectives/Scope

We describe a visual digital twin system to allow for both operation and training of a data-driven pipeline leak detection system. We show system design in terms of its data inputs and the software system which incorporates this data in real time. This system allows visualization of pipeline data and machine learning-driven leak detection in a pipeline sitting in a subsea context. The intended purpose of the system is to both train operators of the leak detection system in its use and also provide high situational awareness to those tasked with monitoring pipeline deployments. The visual digital twin system uses gaming engine technology to achieve high visual quality. We also construct a novel software system enhancement to incorporate live data streams into the gaming engine environment. This allows real-time driving of gaming engine visualization elements with which we may augment the gaming engine environment. In terms of visualization, we focus on addressing problems of large ranges of multiple scales and providing high situational awareness which minimize operator fatigue and cognitive load. We show how multiple camera views in combination with a convenient user interface can help to address these issues. We demonstrate a digital twin system for leak detection. We show its realtime operation in a gaming engine environment with the ability to instantaneously incorporate outside data sources into the visualizations. We demonstrate using simulated pipeline flow data from sensors such as pressure, temperature, etc. This is visualized in the context of a subsea pipeline on a sea floor. Given the large range of scales, we demonstrate how we can view both the full kilometer scale pipeline and smaller subsections in the context of specific sensor data streams. The overall system demonstrates a novel combination of advanced software systems which incorporates real-time data stream with visualization using a high-fidelity gaming engine. The data used represents a leak detection scenario where both operator training and situational awareness are key desired outcomes.
Enhancing Polyethylene Reactor Operation, Efficiency & Process Control Using Online Inference of Polymer Properties: Melt Index & Density
Authors: Kathuria Nishchay
Published: October 2023

The main obstacle to controlling product quality in polymerization reactors is the lack of appropriate online polymer property measurements. In the UNIPOL Polyethylene reactor, a method for inferring melt index and density presented. From the available on-line temperature and gas composition readings, theory-based models are developed to anticipate quality characteristics. Online parameter updates are performed for these models’ movable parameters using infrequent laboratory measurements and back propagation-based parameter estimates. Operating data from LLDPE2 (UNIPOL PE) reactor is used to illustrate how this methodology is applied. These methodologies, when combined with the most recent recursive algorithms, allow inferring crucial polymer parameters, thus enabling way for Advanced Process Control by giving operators the ability to designate set point for the parameter once it has been fully validated. Knowledge of product property deviations from desired targets is required so that plant operators can take corrective actions to reduce the quality of off-grade material and produce consistent quality product.
Improving the Predictive Power of Equation of State Models for Fluid Systems Undergoing CO2 Injection
Authors: Mogensen K.
Published: October 2023

Phase equilibrium calculations require experimental lab data to constrain component properties in an equation of state (EOS) model. These thermodynamics-based models generally perform well when it comes to predicting conventional PVT experiments but often fall short when it comes to predicting gas injection experiments, particularly for CO2 injection. We therefore seek to develop methods that can help provide a good initial estimate of the swelling curve, in cases where laboratory data are not available.

Our company PVT database compromises more than 2,200 PVT studies, which enables us to pursue three different avenues for predicting the CO2 swelling curve. The first method relies on a machine-learning algorithm, which takes fluid composition and temperature as input. In general, we find that this solution does not preserve monotonicity of the pressure-dependent properties and it extrapolates poorly outside the parameter space used for training. As an example, it fails to predict the first-contact miscible pressure defined as the maximum pressure on the swelling curve.

The second option involved correlating swelling pressure, swelling factor and swelling density as a function of the amount of injected gas. We find that all three curves are well-represented by a parabolic expression and we were able to correlate the coefficients as a function methane content in the reservoir fluid only. The resulting model predicts saturation pressure, swelling factor, and density of the swollen mixtures with an absolute average deviation of 4.8%, 2.3% and 1.7%, respectively, which is an excellent starting point for tuning an EOS model for EOR screening studies until experimental data becomes available.

The third strategy involved tuning a separate EOS model to each of the 34 CO2 swelling studies and then attempt to correlate the EOS component properties. We compare the values of the tuned pseudo-component properties against some standard correlations such as Pedersen, Kesler-Lee, Riazi-Daubert and others. We find that the Pedersen correlations for critical pressure, critical temperature and acentric factor provide a more accurate initial guess than the other correlations tested. However, we observed that the tuned solution depended to some extent on the initial guess. We find that for our fluid systems, the default values for the critical volume of the pseudo-components need to be reduced by 15% to better predict the viscosity using the LBC model. Despite the slightly improved property estimation, we did not manage to find a clear trend for the binary interaction coefficient between CO2 and the plus fraction. Therefore, we would recommend predicting the CO2 swelling curve with the set of parabolic correlations.
Khebra Program
Authors: Al Hosani Mariam Abdul Aziz
Published: October 2023

The Khebra Program is a well-structured initiative aimed at utilizing the expertise of subject matter experts (Alumni - former Employees who meet the minimum years of continuous service at the organization) to transfer their knowledge from diverse disciplines across the organization. Through this Program, the company gains access to a vast pool of SMEs from the Headquarter of the organization and it Group Companies, enabling the utilization of their knowledge through short-term consultancy contracts with a minimum period of two weeks to 6 months (extendable as per the business requirement and KHEBRA Committee approval).

The program allows utilizing the experience on a consultancy basis for various matters on full time work basis daily or selected days as per the signed contract and the project scope, including but not limited to delivering know-how for mega projects and future business development as well as sharing their knowledge and training the next generation and maintain a sustainable connection with the organization.

To ensure the effective implementation of the Khebra Program, an advisory committee has been established. This committee holds the responsibility of selecting the most suitable SMEs to participate in the Program, providing them with professional guidance, training, and coaching. The selection process follows specific criteria outlined in the Khebra Procedure, ensuring that only qualified SMEs are enrolled in the Program.
CO2 Storage in a Giant Depleted Carbonate Gas Reservoir -Addressing Feasibility and Design Challenges with Field Data
Authors: Xu Siqing , Al Keebali A. , Baslaib M. , BinAmro A. A. , Ali I. , Vantala A. , El Yosef B. , Abdelazim M. Farouk , Perumalla S. , Mascagnini C. , Benaichaoui F. , Harper C. , Singh H. , Pandya S. , Kasekar H.
Published: October 2023

An integrated study on CO2 storage in a giant depleted gas reservoir was completed. The objectives were to assess feasibility, potential capacity and timing for CO2 storage. Significant design challenges were addressed, including thermal-geo-mechanical impact on cap-rock integrity due to injection CO2 cooling, hydrate, injection well life cycle design and clusters location and surface facilities options. Further de-risking is recommended and ongoing.

An integrated approach was adopted combining/optimizing requirements from reservoir, injection wells, cap rock integrity, surface clustering, CO2 transportation and compression/pumping. Key impacts were accounted for: injection J-T effect, hydrate, stress changes, cap rock integrity, well life cycle design, existing well integrity, costs, and surface facilities. Single well models were developed for injection cooling simulation and well design options. 3D reservoir simulations were performed for reservoir pressure changes, storage options, thermal and geo-mechanics for cap rock integrity. Surface facilities options were evaluated, arrival pressure and temperature impact. Several iterations were carried out aiming at optimizing project economics with uncertainty analysis. Results from a CO2 field injection test are presented, part of key design input.

Detailed 3D reservoir simulations show that CO2 injection start-up timing and ramping up strategy are important: starting early helps additional gas recovery, late would exacerbate injection CO2 J-T cooling. Placing CO2injectors further away from producers helps enhanced gas recovery. The results of an extended actual field CO2 injection tests are presented, showing downhole temperature changes with injection rate and transient stabilization. Existing well logs and stress profile measurements were combined. Single well models were developed to simulated cooling around well-bore. Velocity strings, small tubing sizes, are potential injector design options. Hydrates formation was found in certain scenarios. Thermal-Geo-mechanics analysis show appreciable stress changes possibly propagating > 150m into cap-rock. Although CO2 surface arrival temperature can be boosted by installing heaters, but would incur higher costs and additional requirements on wellhead design. It became apparent that individual subject requirements would affect the overall design. An iterative-looping integrated approach was adopted with CO2containment and maximizing project economics as over-riding objectives. Overall CO2 storage capacity was maximized. Adequate field data/measurements are essential and critical modelling input. Further de-risking recommendations include core laboratory geo-mechanical testing, further CO2 field higher rate testing, and comprehensive existing well integrity assessment.
Testing Of Production Profile Monitoring in Multi-Stage Fractured Horizontal Wells of Changqing Oilfield, China: Based On the CT-Conveyed ESP
Authors: Lu Hongjun , Liu Guangsheng , Li Dajian , Yang Haitao , Gan Qingming , Zhu Hongzheng , Cui Wenhao , Su Zubo
Published: October 2023

For horizontal wells of the Changqing ultra-low-permeability oil reservoir stimulated via the multi-stage multi-cluster fracturing, an innovative production profile monitoring technology, adapted to the long horizontal wellbore and low liquid production, was developed to provide references for adjustment and treatment of production performance of wells.

The presented production profile test method at the stage/cluster scale for horizontal wells uses the coiled-tubing, internally penetrated by a load-bearable multi-core composite cable to connect the small-diameter electric submersible pump (ESP) and FSI production logging tool. The ESP and FSI logger are conveyed to the horizontal wellbore by the cable-through coiled- tubing. The cable-powered ESP drains the wellbore, and simultaneously, the coiled tubing drags the ESP and FSI logger along the wellbore to perform production profiling of frac stages/perforation clusters. The monitoring signals are transmitted via the composite cable to the surface, where the production monitoring, interpretation and analysis are completed.

Increasing the well production rate with an ESP and dragging the tool string for continuous measurement effectively solve the technical challenges of the low success rate and inferior operation efficiency of production profiling in oil wells with low liquid production and extended horizontal wellbores. The test results, combined with near-wellbore and far-field acoustic fracturing propagation monitoring, enable quantified characterization of the production contribution pattern of stages/clusters and also the mechanisms and regularity of water breakthrough of horizontal wells in the case of water flooding. Testing in two wells demonstrates that the presented technology is technically competent for production logging in a horizontal wellbore no longer than 1500 m with various production rates. It provides a new methodology and technical approach for horizontal well production monitoring and interpretation in low-permeability oil reservoirs.

This CT-conveyed ESP-assisted production profile testing technology for horizontal wells represents the first of its kind in the world, in terms of the integration of the cable-through CT operation, ESP artificial lifting and FSI production logging. Multiple challenges were overcome for technical crossover and integration, and the operation code was developed, which are practically valuable for the progress of the testing technology of oil and gas wells.
Comparison of Drilling Rate Penetration Prediction Based on Deep Learning Approaches, A Volve Dataset Use Case
Authors: Djamaluddin B. R. , Mohammed S. A.
Published: October 2023

Efficient drilling operations in the oil and gas field is an important area that can lead to major cost and hazard reduction. One of the key parameters for drilling optimization is predicting the rate of penetration. The penetration rate depends on the physical process which contains variables or features that will affect the values. Using these features, it is possible to predict the penetration rate more accurately during the drilling operation. In this study, we propose comparison of deep learning models between models based on deep recurrent neural network and transformer to predict penetration rate. The result shows that the transformer model outperforms the other models.
Innovative In-Situ Foam Generation and Injection Strategy Using Greenhouse Gases for Conformance Control
Authors: Hanamertani Alvinda Sri , Elkhatib Omar , Yu Ying , Ahmed Shehzad
Published: October 2023

Mobility control is one of the most pressing challenges facing greenhouse gas injection for enhancing oil recovery (EOR). A promising solution for this issue was portrayed in employing foam technology due to its favorable mobility ratio and ability to delay the breakthrough of the injected gases. However, the costs pertaining to the utilization of expensive foaming chemicals have prompted economical complications for the wide scale application of the foam EOR techniques. In this study, we compared different foam injection strategies with the economical aspect in mind and introduced a novel injection approach with superior techno-economic performance in generating CO2 and CH4 foam in-situ at harsh pressure and temperature conditions.

Four foam injection strategies were evaluated in terms of their impact on the mobility reduction of the in-situ generated CO2 and CH4 foams. In the methane foam case, the co-injection mode produced high mobility reduction factor (MRF) compared to the single cycle surfactant alternating gas mode (1-SAG). However, the multicycle strategies including the SAG and the proposed gas alternating foam (GAF) outperformed the co-injection mode yielding MRFs of 289 and 336, respectively. The steady state co-injection of CO2 and surfactant solution, however, produced less mobility control compared to the 1-SAG mode. The multicycle SAG and GAF strategies provided more favorable mobility ratio, with MRFs of 99 and 120 respectively, when compared with the other injection strategies of CO2-foam. Consequently, the novel GAF injection and in-situ foam generation strategy displayed the most prominent mobility control potential for both gases. Besides, this injection strategy decreased surfactant consumption by more than 70% compared to the other injection strategies shedding light on its worth as the most promising economical foam generation strategy in EOR field applications.
Unconventional Cementing Technique to Achieve Good Zonal Isolation in Primary Casing Cementation Jobs for Weaker Formations or Loss Zones
Authors: Khaldy A. , Hassan J. , Gupta S. K. , Baloushi Z. A. , Alqattan F. A. , Datta Abhijit , Monterio Ken , Kunchur B. , Hussain M. Khadar , Ellis Chelsea , Singh R. , Kalgutkar N.
Published: October 2023

This article discusses the big volume top job of oil and gas wells, specifically wells A and B which were drilled in Kuwait. The process involves pumping a larger volume of mixture of cement, water, and other additives into the annulus to seal the wellbore, prevent fluid migration and provide structural support.

The article highlights the need for precision and control to ensure proper placement. The conventional methods like two stage method and lightweight systems used for the wells A and B were not sufficient to get the good zonal isolation throughout the well bore due to the lower fracture gradient observed in this well. The successful zonal isolation was achieved due to pumping large volumes from the annulus.

The wells were under losses before and during the primary cementing process, which was difficult to achieve the desired top of cement (up to surface). To overcome these challenges, the well was cemented in unique unconventional method which is pumping the bigger volumes from the annulus to cover up to loss zone and eliminate any other fluid column in between. Cement Bond Log (CBL) and Variable Density Log (VDL) were taken after a 24 Hrs wait on cement and the results were good, indicating that the wellbore is properly sealed, and the well is structurally stable.

Pumping large volumes of cement through the annulus can be challenging, as it requires a high level of precision and control to ensure that the cement is properly placed. This process is different to that of conventional top jobs carried out by installing cement baskets. The intention of conventional top job methods is to just seal the annulus at surface without paying any attention to mud caps left in the open hole. This has resulted in remedial jobs which has increased the cost or reduced the life span of wells.

One of the key considerations when pumping cement through the annulus is the volumes considered and thickening time. The rate of flow must be carefully controlled to ensure that the cement is properly mixed along with the additives and that it does not become too thick or too thin. In addition, the rate of flow must be adjusted to account for the variations in pressure and temperature that occur as the cement moves through the well.

Cementing also plays an important role in preventing fluid migration. If the well is not properly sealed, there might be inter communication of the fluids which affects the life of the well. The extremely lower frac gradient wells undergo losses Inspite of using the conventional methods (light weight systems and two stage method) and is the reason to follow the unconventional method of cementing from the annulus so that entire well bore from shoe to the surface is properly sealed with cement. This will result in reducing the unnecessary remedial jobs during the life of the well.
A Robust Method for Data-Driven Gas-Lift Optimization
Authors: Gambaretto A. , Rashid K.
Published: October 2023

Traditional simulation-based approach for Gas-Lift Optimization depends heavily on the quality of reservoir and fluid data. Excessive OPEX and man-hours are needed to maintain data integrity and to ensure the models are suitably calibrated. Even then, pseudo-steady-state models do not consider losses due to multi-pointing condition and slugging behavior; and for dynamic multiphase flow simulation, the added complexity and man-hours required to assert accurate results cannot be sustained on a full field scale deployment.

Gas-Lift Optimization essentially relies on the relationship between the Well Production Rate with the Gas-Lift Injection Rate. The objective of the proposed solution is to remove the need for well models, correlations and personnel from the optimization process and to implement a data-driven (model-free) approach that, by focusing just on the relationship of these variables over time is able to find the next best optimized Gas-Lift Injection Rate setpoint and to implement it directly at the wells via an automated local control loop.

This data-driven approach has been compartmentalized and developed as an Edge Application, ran directly on site in an IIOT gateway device. This method has the advantage of providing a predictive response that can be used directly in conjunction with a solver for single-well and multi-well optimization (handling well level and group level constraints by need). The application operates under iterative optimization cycles that progress towards system optimality. Even though well conditions are constantly changing over time, and consequently system optimality, these changes are reflected in the high-frequency data gathered by the application running on the gateway on site. Due to the iterative nature of the process, the solver can recognize these changes and react accordingly, adjusting based on the new system conditions in a closed-loop manner.

This paper presents the methodology and the results of a case study of eight wells, including both, single and multi-well optimization. All these wells are unconventional horizontal wells from the Permian basin in Texas, US. Regardless of the complexities associated with unconventional wells, noted by severe slugging and fast changing well conditions, in all the cases the results were outstanding. For the single well optimization, the candidate well was able to outperform the remaining wells in the pad by 5% in production improvement. For the multi-well optimization results vary from 5% to 25% production improvements. The full execution and optimization process was done in a fully autonomous manner, removing completely office and field personnel, as well as the need for well modeling from the optimization process.

This solution demonstrates a fully autonomous and Data-Driven Gas-Lift Optimization workflow, from data gathering and processing, edge computation, multi-well optimization based on field constraints, to the direct well implementation via closed-loop control.
Novel Combination Iron Sulfide-Corrosion Inhibitor Development, Testing and Field Assessment for an Integrated Scale Management System
Authors: Okocha Cyril , Obeyesekere Nihal
Published: October 2023

This paper concerns wet gas production in East Texas area highlighting the use of an innovative approach to solve a unique severe scaling challenge with a cooperative operator. The scope of application spans some 1,200 wells in the Central and East Texas area where the challenge was gas production with associated corrosive fluids in low pressure condition, leading to significant deposition of carbonate and iron sulfide scale within the production tubing. This paper details unique challenges and solutions in developing a single lift chemistry that prevents inorganic scales, particularly iron sulfide scale in the production tubing whilst providing adequate lift to the well. Development work presented includes laboratory and field foamer testing, anoxic iron sulfide scale testing, and autoclave corrosion testing. This was made more challenging due to the high downhole temperatures of 300°F with a pressure of 1,000 psi and a mixed sweet / sour gas with a composition of 2.2mol% CO2 and 0.75mol% H2S. Testing showed that application of these products at 2,000 to 4,000 ppm were able to stabilize gas production, reduce the corrosion to acceptable corrosion rates and prevent the deposition of iron sulfide scale in static and dynamic tests. Extensive detail is provided during the field trials and the monitoring regimen that was put in place to monitor all functionalities provided by this chemistry. As this was across a whole host of different well types significant data was generated and a wealth of information and lessons learned for the industry can be extracted from it. The paper concludes with the overall lessons learned and summary of the validity of this technology and how it could potentially be a game changer for the industry at large in East Texas where gas well deliquification combined with corrosion and scale formation is a shared challenge.
Adopting Cost Effective Cutting-Edge Technology to Mitigate Cemented Annulus Pressure and Reduce Carbon Footprint
Authors: Abdi R. M. , Alhosani A. H. , Sumaida Ali. S. Bin , Ahmad M. H. , Alshehhi H. , Altamimi A. , Issa F. H. , Elrefai F. M. A. , Barker D. , Murty M. J.
Published: October 2023

Sustained casing pressure (SCP) is one of the major well integrity challenges. A variety of annular pressures exist in the wells. Well integrity teams strive to ensure that once the well is flowing at steady state conditions, the pressure from all casing strings should be manageable as low as possible below the Maximum Allowable Annulus Surface Pressure (MAASP). If the annular pressure builds above this level, then the casing exhibits unacceptable SCP. The impact of SCP can develop to critical consequences if not timely managed and brought to an acceptable level.

This paper describes a new approach in controlling SCP using a technique with a high-density, solids-free, non-corrosive, environmentally approved, low-viscosity fluid to control and substantially reduce SCP to acceptable operating levels. The focus of this paper is to demonstrate how to mitigate SCP in the cemented annuli. Production (tubing and packer) and un-cemented annuli are not covered.
Impact of Change in Mud Weight & Offset Well Injection Pressure on Cement Sheath Integrity; Case Study for UAE Offshore Field.
Authors: Elhassan Azza , Manga Patrick , Abdellatif Mohamed S. , Hamidzada Ahmedagha , Andrews Kerron , Takahiro Takahiro , Sherif M.
Published: October 2023

As drilling horizontal wells became more complex with multiple production drains from various reservoirs, zonal isolation has become a key challenge to be achieved. Many studies have shown the impact of change in mud weight during drilling activities on wellbore stability, without considering the consequences on the set cement. This case study will be focusing on drilling activities on offset wells, evaluating & exploring how mud weight changes can affect wellbore instability and damage the cement sheath despite the fact that the cement evaluation logs showed good results days after the cement job and before the mud weight reduction.

The wells being studied have been analyzed using Finite Element Analysis (FEA) modeling after the cement was set and exposed to a change in mud weight as well as being exposed to the offset injection well. FEA computer simulations have enabled this modelling to determine the optimal mechanical properties required for the cement slurries to withstand those load limits (pressure testing, pressure reduction due to change of mud weight or an increase of the pore pressure due to an offset injection well). After opening the window and drilling ahead through the production drain wellbore, the wells have the same tendency of instability and require an increase in mud weight to control the inflow.

This paper presents the impacts of the offset wells and the change of mud weight on the cement sheath failure in debonding, cracking, or sheath deterioration leading to gas channeling due to a micro annulus. The considered wells present the same behavior that has been highlighted above. The question to ask is why did a well that has been cemented and recorded a good cement bond fail to provide proper zonal isolation? The injection pressure of the offset well was evaluated and then used in the simulations, considering the conventional cement used during the primary cement job. The analysis has shown a complete failure of the cement integrity: cement debonding from the casing or from the formation; cement cracking and sheath failure.

The cement slurry with improved mechanical properties was employed for the study under the same pressure conditions from an offset well and mud weight change. The model results demonstrate that the new cement's ability to withstand stresses has improved on the wells cemented after this study.

The modelling effort presented in this paper allows for a barrier to be designed that has enhanced mechanical properties compared to the already placed barrier on the offset wells in the same field. Aside from improving the set cement mechanical properties, the mud weight change design has been improved in such a way that the mud weight must be anticipated, decreasing its impact on the barrier.
Challenges in Drilling and Completing Extended Reach Drilling Wells with Casing Design Optimized from Conventional Ones
Authors: Unnikrishnan N. K. , Alnuaimi M. , Al Suwaidi M. , Al Yamani S. , Bahumaish M. Jamal , Al Karbi H. , Salem G. , Al Ameri S.
Published: October 2023

Well was drilled in Al Nouf field with the objective to increase the sustainable production across Kharaib-2 formation. This paper presents the challenges faced in planning and drilling of subject well penetrating multiple reservoirs with only two casings. Later 4000ft horizontal hole was drilled in the same reservoir and completed with PPL lower completion.

Planning of this well commenced by meetings and collaboration with multiple disciplines such as Drilling, Integrity, technical center and Asset team with the common objective of drilling and completing a horizontal oil producer well in less duration and cost without compromising the integrity of the well. All the associated risks were highlighted and mitigated by proper planning and engineering analysis such as casing design, trajectory, collision risks, BHA, torque and drag and hydraulics. Management of change was issued and approved by all stake holders for deviating from the normal casing design as per company operation guidelines.

This ERD Oil Producer well is the first well in the field to successfully complete in only two casings sizes. This paper will explain the innovative and novel approach of mitigating the challenges faced while drilling a complex well of 7,400ft departure with two casings and have a horizontal section of 4000 ft with 8-1/2" drainage and completed it with 6-5/8" PPL lower completion. The main challenges were penetrating the total loss zone along with unconsolidated shallower formation in surface section and drilling the permeable reservoir with high mud weight OBM due to highly unstable shale formation above it. These challenges were immaculately mitigated with advanced engineering analysis and close supervision while execution. Results from this well have proven that having lower completion in ERD wells have significantly improved the well accessibility and well performance and enhanced the reservoir management and thereby reducing the field development cost without affecting the well integrity. This paper summarizes the practice and technology used to successfully drill the ERD well in artificial island with two casing sizes.

The challenges and its mitigation explained in this paper will support the idea to further drill and complete the well with minimum number of casing sizes. Thereby more number of wells can be drilled in less number of days and well cost.
Holistic Approach of Acid Stimulation Selection in Carbonate Fields for Productivity Enhancement
Authors: Sarsekov A. B. , Ryan A. , Kamaletdinov B. , Arali V. , Araque G.
Published: October 2023

Carbonate rocks constitute a significant portion of hydrocarbon reservoirs worldwide. Due to their unique geological deposition, carbonate formations have different ranges of heterogeneities such as mineralogies, permeabilities, fluid properties, fissures, natural fractures, and reservoir pressures. On top of their inherent heterogeneities, well operation activities such as drilling and well intervention can damage the formation. In the lower-permeability formations, a maximum reservoir contact (MRC) well is a preferred option to extract hydrocarbon from the reservoir. An MRC well involves specific challenges from the well completion perspective that eventually could impact the productivity.

Carbonate stimulation is a long-standing technique to increase productivity in carbonate formations. Stimulation treatment in general improves the hydrocarbon deliverability to the wellbore and eventually to surface. It also removes or, on some occasions, bypasses the damage in the wellbore. With a long horizontal well, more surface area must be stimulated; however, more surface area means there is more heterogeneity to overcome as well. This paper describes the importance of acid stimulation planning as well as modeling, which plays a vital role in effectiveness of acid stimulation job in horizontal wells with different MRC completion types and achieving the best results of productivity enhancement in carbonate fields.

Log-and-completion-based simulation software was used to model the formation heterogeneity in combination with well completion complexity. Different modeling scenarios based on well trajectory and completion design are simulated together with the reservoir heterogeneity such as different permeability, possible fissures, different reservoir pressures. Different acid systems are also simulated against these heterogeneities and complexities. The stimulation modeling results show that stimulation uncertainties arise when both completion complexity and reservoir heterogeneity are present.

A stimulation integrated workflow following the stimulation design workflow in the latest log-and-completion-based software is presented. Some case studies in UAE related to these challenges are presented with some key lessons learned. Some advanced carbonate acidizing technologies are implied in this observation to achieve the stimulation objectives.
i-Geo Sensing: An End-to-End Fracture Direct Diagnostic Platform
Authors: Van Pham Vuong , Dahaghi Amirmasoud Kalantari , Babakhani Aydin
Published: October 2023

Within the development of unconventional resources, especially in the United States, multi-stage hydraulic fracturing across multiple fields is adapted to become the best practice in the industry. In hydraulic fracturing, a complex fracture network is always initiated before the slurry fluid is pumped into the reservoir. Consequently, understanding this fracture network's geometry and its degree of complexity has been one of the forefronts of unconventional development. The industry has been conducting various methods to achieve this forefront, divided into three categories: direct near-wellbore (e.g., production/temperature logs, tracers, borehole imaging), direct far-field (e.g., micro-seismic fracture mapping), and indirect modeling (net pressure method). Unfortunately, none of these methods provide direct and dynamic information about the hydraulic fracture network.

In this study, a novel integration of both hardware (namely, the Smart Microchip Proppants, abbreviated as SMPs) and software (namely, the i-Geo Sensing) is conducted to address the "indirect" drawback of current fracture diagnostic techniques and practicalize the power of modern Deep Learning in semi real-time fracture mapping. The SMPs are explicitly designed to be injected directly into the reservoir along with the conventional proppants. This paper focuses on the transmitted smart microchip proppants data in semi-real time. The i-Geo Sensing is integrated between three core modules: the unsupervised, the supervised, and the connector. The unsupervised module digests the transmissible signal from the SMPs, performs necessary pre-processing, and recognizes prospective fractures. The supervised module receives the result from the unsupervised module, combines with the support from the data generator module, flow-back/production data, and eventually predicts the most reasonable realizations of the hydraulic fracture network.

The i-Geo Sensing's capability is tested using a case study with the pre-defined hydraulic fracture geometry. Results from the case study indicate the robustness of the supervised module under unknown loss of data transmission from the SMPs (2-5% decrease in accuracy) and consistent improvements of accuracy between 9-25% in fracture diagnostic from the unsupervised module to the supervised module.
Cross Functional Improvements in Modelling Complex Carbonate Reservoirs
Authors: Wahbah S. , Almheiri A. , Hattori T. , Alhosani F. , Farmer R. , Gacem M. T.
Published: October 2023

Geological Modelling (GM) of heterogeneous carbonates can be challenging to history match with actual reservoir performance. Reservoir heterogeneities that present challenges to history match production include High Permeability Streaks (HPS), Stromatoporoid layers (STR), Fractured Dolomites (FD) and in this reservoir, extensive porosity-deteriorated bitumen-affected volumes. Local experience and knowledge help address model limitations and inconsistencies, and correlating diverse data types is critical to bridge gaps when uncertainties compound: this case study details multi-disciplinary improvements of such GM.

3D seismic was reprocessed to improve signal-to-noise ratio (SNR), fault interpretation and AVO/AVAz and seismic attributes, stochastic inversion, and rock physics analysis was used to improve facies and porosity modelling, facilitated by a strong, three-way relationship between Acoustic Impedance, porosity, and STR layers. In addition, newer horizontal wells with wellbore images helped improve the understanding and distribution of STR and bitumen presence and validated the updated seismic fault interpretation. 3D seismic inversion identified a top bitumen surface scenario that was supported in well observations. Refinement of the stratigraphic framework, zonation and layering captured heterogeneities including vertical and lateral lithofacies distributions and sequence boundaries, and an updated rock typing (RT) scheme characterized reservoir heterogeneities (HPS & Bitumen presence).

Updated Saturation Height Function (SHF) and Free Water Level assumptions accommodated the new structure and RT scheme. Multiple models were tested to characterize saturation models from Pc curves and statistical analysis of saturation residuals and hydrocarbon pore thickness was used to assess and rank model performance. The selected SHF model was based on model efficacy on multiple scales from field, domain, wells, layers and by RT.

Integrating multi-disciplinary data types to resolve reservoir challenges is a crucial aspect to deliver fit for purpose geological and dynamic models in mature fields. This case study illustrates the value of merging geophysics, stratigraphic, lithologic and petrophysical data and analysis to update model properties and performance and identify and address uncertainties.