bluuebunny/crossref_metadata_2025 huggingface dataset:
Flood Management: Solving Conformance or Sweep Efficiency Problems—Part 4: An Overview of Solution Research and New Technology
Authors: Smith David
Published: October 2023

The first three articles in this series have discussed problem identification, problem understanding; solution design, execution, and performance; and benefit methods and techniques that should help in our efforts to improve the solution success rate, but we still have further improvements to make.

Part 4 provides an overview of ongoing research and recent technology improvements focused on improving sweep efficiency or conformance solutions taking place in both academia and the service industry within the US. This article does not review efforts taking place inside oil production companies or national oil companies as that work is generally not publicized until completed.

Before we start this review, let’s capture some thoughts that were expressed by several department chairs and other leaders in the industry. There is a common feeling that the level of research activity on all conventional oilfield recovery problems has suffered from a change in interest and funding over the past 10 to 15 years.

Research on conformance or sweep efficiency problems is a subset of conventional oilfield recovery issues and thus has also suffered from this reduced interest. Instead, a significant rise of unconventional oilfield recovery needs and focus on greenhouse gases (GHG), carbon footprint, and the energy industry transition has shifted the priorities at many universities, governments, and service providers. This shift in efforts has resulted in a significant redistribution of resources that were once focused on conventional oilfield recovery issues.

The number and types of conventional oilfield recovery problems has not changed; if anything, they continue to grow, but the addition of unconventional resources and their unique character, along with the push for studies on GHG, carbon footprint, and energy transition without a corresponding increase in funding and manpower has diluted our ability to respond as an industry to these needs.

This perspective is offered as a simple observation of conditions that exist in the energy research arena. No judgment is made on the appropriateness of this change or the overall situation. Simply be aware that as an industry we have many challenges to face in the future and some will suffer as others are prioritized.

As a result of this and some other reasons, several universities such as Colorado School of Mines, Louisiana State University, Penn State, Stanford University, University of Houston, University of Southern California, The University of Tulsa, and University of Wyoming are not reporting any active or current efforts on conventional asset sweep efficiency or conformance solution research. This does not mean that all interest in these technologies has been lost, only that no current research activities are underway. This is unfortunate, but I believe it is representative of this industry shift.

Now, back to the primary focus of this article.
Case Study: Gas Lift-Plunger Lift Combination Creates Full Life Cycle Production Solution
Authors: Cope Brent , Gilmore David
Published: October 2023

From the Wolfcamp and Bone Spring in the Permian Basin to the Niobrara and Codell in the Denver-Julesburg Basin, lateral lengths of 10,000 ft or greater are becoming the norm in tight-oil resource plays (Rassenfoss 2022; Addison, 2021; S&P 2021).

From a production standpoint, longer laterals equate to greater stimulated rock volume per wellbore. That means higher flow rates, but it can also introduce more dynamic behavior and steeper production declines. The extended-well trajectories are often accompanied by high dogleg severities, high gas/oil ratios (GORs), and sand and solids production (Whitfield 2023; S&P 2021).

Efficiently accommodating all of these factors while cost-effectively managing natural declines over time can be a challenge for any single artificial lift method. However, the combination of gas lift and plunger lift technology gives operators a flexible option to optimize production beginning with initial peak flow rates at the start of production and extending all the way through to depletion.

This “full life cycle” approach encompasses three distinct phases that collectively span the entire slope of the tight-oil well decline curve:

- Gas lift in early to mid-life (from first production to ±300 B/D)

- Plunger-assisted gas lift (PAGL) in the mid- to late-life plateau (from ±300 to ±100 B/D)

- Plunger lift in late life (from ±100 B/D to last oil)

An artificial lift approach leveraging gas lift, PAGL, and plunger lift at different points along the production timeline aggregately brings the key advantages of all three to bear in horizontal tight-oil wells, including

- Gas lift’s ability to mimic natural reservoir flow, lifting fluids to surface by reducing the flowing tubing pressure and creating differential pressure between the reservoir and wellbore. Gas lift handles an array of production rates (up to 2,000-plus B/D) and well characteristics—including high GORs and solid content—and can adapt to rapidly changing conditions during early well life.

- PAGL’s ability to increase reservoir drawdown, stabilize production, and reduce system surging as production diminishes to the point where gas lift starts to become inefficient in the mid-life phase.

- Plunger lift’s ability to use pressure buildup below the plunger to carry accumulated fluids to surface at rates as low as a few B/D, requiring no external power source to surface the plunger. The plunger creates a “swabbing effect” as it passes through the tubing that helps draw fluids from perforated intervals while keeping tubing swept of paraffin, scale, asphaltene, sand, etc.
Technology Focus: Offshore Drilling and Completion (October 2023)
Authors: Jayakumar Swathika
Published: October 2023

Optimizing and continually increasing efficiencies at every stage of the drilling and completion process are central themes in the papers showcased in this feature. Innovating our way through difficult times is what the oil and gas industry excels at, especially during challenging periods. During the COVID-19 pandemic, the offshore energy industry faced immense struggles with high upfront capital investment and long lead times in uncertain circumstances with extremely low oil prices.

The challenges brought about by the pandemic served as a backdrop to many of these innovations. Companies were compelled to discover creative solutions to maintain efficiency, reduce costs, and ensure safety during an era of unprecedented disruption.

Innovation in advanced analytics and machine-learning algorithms is used to optimize drilling-center locations, leading to cost reduction. This development became even more critical during the pandemic as companies aimed to maximize efficiency and minimize expenses. The execution of large-scale projects such as the Johan Sverdrup development highlights innovation in project management, enabling timely and cost-effective operations in a challenging environment. The emphasis on digital solutions and fiber-optic technology in Guyana’s offshore operations illustrates the industry’s adaptation to the pandemic by enabling remote operations and real-time data collection while maintaining efficiency in a new discovery.

Innovations in riserless light well intervention systems are particularly relevant during the pandemic. These systems improved efficiency and safety for offshore interventions, enabling the industry to operate with minimal personnel onboard. The focus on well-planning strategies to overcome challenges in deep depleted reservoirs includes approaches that optimize drilling in complex conditions, which is crucial when efficiency is paramount. Retrofitting autonomous inflow control devices proved an effective approach in implementing state-of-the-art technology to improve reservoir sweep and productivity.

Moving forward, this innovative spirit in our industry as seen in these papers is a testament to our resilience during challenging times. In the coming years, this ability to sustainably increase recovery efficiencies to ensure energy security is crucial to shaping the future of energy production.

Recommended additional reading at OnePetro: www.onepetro.org.

SPE 212499 4D Radar Imaging of Wellbore Geometry While Drilling by Lars Øy, Well ID, et al.

OTC 30979 Guyana Operations and First Oil by Mike F. Ryan, ExxonMobil, et al.

SPE 212915 Enhancing Riserless Light Well Intervention Operability From Operator Perspective by Michael Long Ge, BP, et al.

SPE 214057 Challenges of Drilling Deep Wells in a Complex Overburden With Severe Depletion and Experiences From Caspian Sea by Anwar Juma Al Saadi, Dragon Oil, et al.
Retrofitted Autonomous Inflow Control Devices Optimize Completions Design
Authors: Carpenter Chris
Published: October 2023

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31301, “Optimized Completions Design Using Retrofit Autonomous Inflow Control Devices,” by Ezinne A. Nnebocha, Schlumberger; Akinola Akinbola, NPDC; and Omagbemi G. Kayakor, First Hydrocarbon Nigeria, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission.

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Discovered in 1964, the Beta Field in the Niger Delta sedimentary basin consists of 25 stacked hydrocarbon-bearing reservoirs between 5,500 and 12,000 ft true vertical depth subsea (TVDSS). Oil production peaked at 8,900 STB/D shortly after field startup and has been on the decline. Two horizontal wells, Beta 7 and Beta 8, were planned in the field, but a production forecast of the planned wells showed potential early water breakthrough and high water cut. Autonomous inflow control devices (AICDs) were deployed successfully in the Beta Field for the purpose of minimizing water production and maximizing oil recovery.

Introduction

After history matching, the two new horizontal wells were simulated to target the sweet spots in the reservoir using constraints of oil saturation, porosity and permeability limits, and distance to the oil/water contact (OWC). The history-matched model was then used in forecasting the production profile for the new wells using a target liquid production rate of 2,000 STB/D. The production forecast without inflow control showed water breakthrough in the new wells within the first month of production, reaching to 45% within 3 months of production. Cyclonic AICD completions then were simulated for Beta-7 and Beta-8 horizontal wells, which showed improved oil production and delayed water production.

AICD Retrofit Design

Cyclonic AICDs were selected for application in the Beta Field to improve production performance. However, the short lead time required for the job execution and border closures caused by the COVID-19 pandemic created restrictions in mobilizing personnel and equipment from outside the country. It did not appear that the equipment could arrive in time for the job. The conventional nozzle-based passive ICD joints were available in country. Therefore, leveraging engineering skills and operational knowledge, a solution to retrofit AICD nozzles in existing ICD screen joints was conceived.

The engineering team developed a design of machined components that could be quickly manufactured at the facility of the original equipment manufacturer (OEM) and shipped to the location.

Failure-mode and effects-analysis assessment, and subsequent risk-management procedures, became useful to manage the process locally with the help of the remote OEM team. A step-by-step procedure on the retrofit was devised. Fig. 1 shows a flow chart used to guide the retrofitting process and the retrofitted AICD joints after modification. Upon completion of the screen retrofit, the joints were quality-checked and inspected to verify their preparedness for well completion.
Downsizing, Use of Dummy and Venturi Valves Enhance Gas Lift Performance
Authors: Carpenter Chris
Published: October 2023

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213975, “Gas Lift Performance Enhancement Strategies by Downsizing and Using Dummy and Venturi Valves: A Paradigm Shift in Gas Lift Systems Management Philosophy,” by Wael F. Akeil, Ahmed M. El-Bohoty, and El-Sayed I. Abd El-Mawla, Gulf of Suez Petroleum Company, et al. The paper has not been peer reviewed.

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A mature offshore Egyptian field has entered a depletion phase. Most of its gas lift design bases were initiated during production startup and feature standardized sets of large gas lift valve port sizes with narrow spacing. Inconsistent well flow during reservoir depletion adds complications to the system. Therefore, a screenout model was created to select candidate wells for downsizing and for changing out with dummy and Venturi valves. After screening, 70 wells were selected for application of the new strategy. The complete paper discusses the effectiveness of smaller port sizes and the use of dummy and Venturi valves in enhancing gas lift performance and maximizing recovery.

Field Background

The field is divided into four main geographical quadrants, each with its own facilities. Total production currently is approximately 60,000 BOPD with an average water cut of 85%.

Exploration and development of the field saw the drilling of more than 460 wells; half of these currently are experiencing reservoir pressure decline, drained reserves, or operational problems. Most wells are gas lifted, and the remainder either use electric submersible pump (ESP) installation or flow naturally.

The facility consists of 73 offshore satellite platforms containing the wells—both oil producers and water injectors—connected to nine offshore complex platforms.

As a part of continuous improvement trials, the operator reviewed the process of gas lift system management to introduce necessary improvements and recommend changes for long-term plans. The proposed amended management system was the result of monitoring, troubleshooting, and optimization activities outlined in the complete paper.

Amended Gas Lift Management System

Using Dummy Valves in Gas Lift System. Conceptual Phase. A dummy valve is a special gas lift valve shaped like solid metallic bar with upper and lower packings. They are installed to replace unloading valves that are no longer needed. Installing dummy valves instead of the unloading valves can reduce problems such as valve interference and deepens the point of gas injection.

Redesign Procedure Based on the New Production Profile. This practice can be applied in two main cases: First, if reservoir pressure has declined and the well is producing with a lower rate but the surface injection pressure is still high enough to reach deeper valves; and, second, if the well is planned to be recompleted from one formation to another that has a higher reservoir pressure but with lower formation feed as the result of lower productivity. The main steps for redesign are provided in the complete paper.
Technology Focus: Data Analytics (October 2023)
Authors: Yang Junjie
Published: October 2023

Throughout the present decade, the oil and gas industry is experiencing and enduring digital transformation, marked by continuous evolution. In the pursuit of increased efficiency, companies have embraced cutting-edge technologies in artificial intelligence and big data, effectively automating their existing work flows.

Having undergone extensive exploration and refinement, the debate between physics-based models and data-driven models has now found a harmonious middle ground. This convergence has paved the way for significant advancements in the realms of transfer learning and machine-learning-assisted simulation, opening up new avenues for research and practical application.

The paramount objective of data scientists in the oil and gas industry is to decipher hidden patterns within the data and subsequently transform these insights into domain knowledge, which, in turn, guides operation and facilitates educated decision-making. Hence, despite the thrilling advancements in deep learning and large language models, the upstream industry continues to extensively use traditional machine-learning models such as tree-based algorithms for processing structured data sets because of their strong interpretability.

Another prominent trend involves the widespread development and application of no-code or low-code machine-learning platforms, empowering citizen data scientists to efficiently leverage machine-learning models.

As we press forward, we are confronted with a series of challenges, including the following:

- Coping with an abundance of data with low quality that need significant effort in manipulation and quality control

- Contending with the relatively high cost of data acquisition, which curtails the full exploitation of data-hungry models

- Encountering a scarcity of successful proof-of-concept projects that make it to production

- Lacking interpretability of complex but powerful models, hindering our ability to deliver tangible insight to subject-matter experts and management

The selected list of papers shares some interesting examples to showcase the value added by close collaboration between data scientists and subject-matter experts and how the power of the digital revolution actively revitalizes our industry.

Recommended additional reading at OnePetro: www.onepetro.org.

SPE 204712 Data-Driven Solution for Enhancing Workover Intervention Activities by Saniya Karnik, SLB, et al.

SPE 211363 Generation of a Regional Fluid Database for Gas Condensate Assets in a Thrusted Carbonate Environment of the Northern Emirates by Harshil Saradva, Sharjah National Oil Corporation, et al.

SPE 211719 Machine-Learning-Assisted Well-Log Data Quality Control and Preprocessing Lab by Nader Gerges, ADNOC, et al.
Data Analytics Enables Reconstruction of Missing Segments in Well Data History
Authors: Carpenter Chris
Published: October 2023

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 208137, “Reconstruction of Missing Segments in Well Data History Using Data Analytics,” by Yuanjun Li, SPE, and Roland Horne, SPE, Stanford University, and Ahmed Alshmakhy, SPE, ADNOC, et al. The paper has not been peer reviewed.

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The problem of missing data is a common one in well-production records. An incomplete data set is commonly simplified by omitting all observations with missing values, which can lead to significant information loss. In the complete paper, the authors developed an efficient procedure that enables fast reconstruction of the entire production data set with multiple missing sections in different variables. Ultimately, the complete information can support the reservoir history-matching process and production allocation and can develop models for reservoir performance prediction.

Introduction

Missing values are a prevalent issue in pressure transient analysis. Their occurrence is often unavoidable and is a serious problem because many data-mining algorithms cannot work with data sets that are missing values. Sources of missing field data include operational problems, changes in operating conditions, and variable sampling frequencies.

Imputation Technique of Missing Values

Case Deletion. If a missing data problem exists in a multivariate series, the time series may not be evaluated appropriately. In time-series data, each record is unique. Thus, deleting a record would result in a series with gaps, which would be unusable for many analyses. Furthermore, the time-series plot would be truncated and riddled with flaws. Thus, to conduct a time-series analysis, those missing observations must be estimated and reinserted. When the number of missing values in the data set is considerable, eliminating the associated cases might result in the loss of vital and valuable information. Researchers have found that case elimination is not appropriate when the missing rate is greater than 3%.

Physics-Based Imputation. Any physics-driven diagnostic or model is based on fundamental assumptions that may or may not be correct in all situations but are intended to represent reservoir behavior. While data-driven models do not make any assumptions about underlying physics, they rely on training data. Therefore, data analytics and machine learning can be an ideal substitute.

Local Statistical Approach. Local statistical methods include the K-nearest-neighbor (KNN) imputation and local-least-square imputation, two of the most well-known algorithms. To impute the incomplete data, the KNN imputation employs a pairwise correlation between the target gene with missing values and the K closest reference genes. For missing-value imputation, the techniques in this local method use local similarity patterns in the data sets or a specific column of data.
Deep Learning Enhances Transfer Learning for Tight-Oil Production Prediction
Authors: Carpenter Chris
Published: October 2023

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 2021-5688, “Physics-Assisted Transfer Learning for Production Prediction in Unconventional Reservoirs,” by J. Cornelio, SPE, S. Mohd Razak, SPE, and A. Jahandideh, University of Southern California, et al. The paper has not been peer reviewed.

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A physics-assisted deep-learning model is presented to facilitate transfer learning in unconventional reservoirs by integrating the complementary strengths of physics-based and data-driven predictive models. The developed model uses a deep-learning architecture to map formation properties to their corresponding production responses using a low-dimensional feature space representation. The results indicate that physics-based simulated data can facilitate production predictions when out-of-range (unseen) input parameters have to extrapolate from data and that transferring the weights learned from the source field to the target field can add valuable information to enhance the prediction performance of the target field.

Introduction

While the limitations of simulation models make them unreliable for developing unconventional reservoirs, the increasing number of wells drilled in recent decades has provided an extensive database for tight oil horizontal wells. The use of such large data sets has permitted the use of data-driven proxy models. These models rely on estimating the approximate functional input/output relations by using various statistical and mathematical techniques. Neural networks are one such type of model designed to emulate neurons in the brain to find patterns within data that have complex relations. Implementation of data-driven proxy models has been used in the characterization of both unconventional and conventional reservoirs. However, these models cannot extrapolate data outside the training-data range.

Transfer learning is one way in which a data-driven model trained on a large data set can be used to learn relevant and common features to solve a specific task with a given source data set. These features are then transferred to build a different model for a target data set with a similar problem definition. The method proposed by the authors attempts to take the benefits of both physics-based simulators and data-driven proxy models to build a more-robust model that can be transferred to build a reliable proxy model for a new field with limited data.

In the model presented in the complete paper, all discrepancies between the simulated responses and field production data can be compensated. Then, the model is transferred to a second neural network designed to be a proxy model for the target field with much smaller data. The neural-network model will attempt to capture the correlations between its formation properties and the difference in production responses from this field. The equations vital to this process are provided in the complete paper.
Automated Work Flow for Sand Prediction, Monitoring Improves Operational Efficiency
Authors: Carpenter Chris
Published: October 2023

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 22989, “An Automated Work Flow of Simplified Representative Elementary Volume Approach to Sand Prediction and Control Monitoring Using Web-Based Interfaces To Reference With Operational Efficiency Improvement in Zawtika Field, Myanmar,” by Supha-Kitti Dhadachaipathomphong, Prapong Sooksawat, and Pooritat Toprasert, PTTEP, et al. The paper has not been peer reviewed. Copyright 2023 International Petroleum Technology Conference. Reproduced by permission.

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The objective of the study described in the complete paper is to increase operational efficiency by using a sand-prediction model to estimate sand production per well based on current operating conditions and to calculate a sand-operating envelope for each well to guide planning and management. The authors found that the simplified representative elementary volume (SREV) approach to sand prediction and control monitoring (SPCM) resulted in an improvement in operational efficiency by reducing time spent on manual analysis and decision-making through dashboards with predictive results. The reader is encouraged to review the complete paper, which contains detailed work flows that include associated equations and steps.

Study Objective

- Implement SREV approach

- Use a sand-prediction model to estimate sand production per well based on current operating conditions

- Estimate sand accumulation from the wellhead to the inlet separator dynamically

- Predict wall thickness of the main flowlines from the wellhead to the production and test manifold

- Forecast sand production when considering changes in reservoir conditions

- Use an automated work flow to run the network model and obtain flow conditions, generate the well’s sand-prediction model based on well design and reservoir information, and calibrate the well’s sand-production models based on the latest validated test or sensor data

- Implement Web-based interfaces

Study Area

The Zawtika gas field is in the Gulf of Moattama, Myanmar. A total of 123 wells and 11 platforms was used in the study. Some wells suffer from sand production because the sands are unconsolidated or weakly consolidated from Pliocene to Pleistocene geologic sequences. Sand production causes severe problems such as reduced well productivity and gas potential and damage to surface equipment such as choke, pipeline, and production systems.
Self-Ignited People Development Via Technical CoPs - Optimum Engagement Strategies to Foster the Full Potential of Our Local Staff
Authors: Drumond J. D. De Sousa
Published: October 2023

Developing local resources and effectively transferring knowledge from seasoned professional and among local staff continue to be key elements and enablers for continuous creation of value in a transitioning energy sector where sustainability, diversity, equality and inclusion are in the spotlight more than never before. This paper continues the work on SPE-210844-MS and SPE-210961-MS, presenting new actions and verification, showcasing outstanding engagement and sustainability figures from 20 months of continuous activity and data analysis. How the strategy can be re-used and extended Is also presented.

Further integration of the Ecosystem for the C&I (Control & Instrumentation) CoP (Community of Practice) was at the heart of the work. Strong emphasis on the Navigability, Mesh Interconnection between objects, Adaptability, Diversity and Flexibility was given. A point of Attention was introduced to eliminate the "Time Zone Bias", which has been identified as an unintended discriminatory effect of global teams that are located in country sites far between them. The use of Heat-Maps analytics was employed as a verification/validation element that the effect was effectively canceled. More than 50 variables were employed to provide mathematically consistent KPIs.

Quantum leap effects were immediately observable after the changes and enhancements were introduced. The level of engagement and utilization could be verified on several fronts. A few of these results included: 1) An enormous growth in the number of "Unique Active Users" of the Knowledge Transfer platform for the C&I CoP, which gradually and steadily increased by more than 1768 %. 2) A sustained increase of monthly average time invested on Learning and Knowledge-Transfer activities by total monthly Users. 3) Use outside working hours (staff investing their own time on self-ignited development) shows remarkable figures, including Saturday and Sunday use of the CoP´s Knowledge Hub. 4) Monthly utilization level (% of time the C&I CoP was being used out of the 24/7 existing time slots) averaged 72%, even without the need to introduce "Special live knowledge transfer events". 5) Monthly average of "Unique active users", as well as many other interesting figures and finding are explored on the paper.

Data Analytics was employed to ID factors that positively affected the level of sustained utilization of the platform, as well as the level of engagement of "Unique active users". A deep understanding and modeling of multiple operational contexts and working environments of users of the CoP allowed to eliminate potentially discriminating factors. The modelling of competence needs against ongoing activities facilitated to proactively discover temporal Gaps and introduce development objects that effectively tackled those needs.
Sedimentary Evolution of Delta and Reservoir Distribution Under the Control of a Volcanic System
Authors: Hou Dongmei , Li Chao , Gao Pengyu , Yuan Xun , Zhang Xiaolong , Cheng Zhong
Published: October 2023

The BZ34-9 oilfield is a clastic reservoir discovered in the Oligocene strata in the southern part of the Bohai Bay Basin. The volcanic system here is intermixed with a clastic reservoir that spans more than 1000 meters. In its upper part, it overlies about 2000 meters of Miocene strata. Volcanic activity has influenced the deposition and filling of the lacustrine and played a key role in controlling the distribution of clastic reservoirs. Based on 3D seismic data and lithological data from 74 wells, four types of volcanic were identified and extracted according to seismic sequences. Establish and clearly state the reciprocal relationship between volcanism and sedimentation.

The study of volcanic stratigraphic framework reflects the environmental change of volcanoes from terrestrial to marine, which is consistent with the understanding of the sedimentary environment from paleontological and sedimentary facies studies. Small-scale volcanism predates the formation of the early Oligocene strata, and a regional eruption center to the south and east of the BZ34-9 oilfield provides the tectonic setting for the basin evolution. The early Oligocene strata was deposited in a shallow lake environment, thin-bed distributary channels are developed in the near-source facies belt near the central volcano, and thick-bed mouth dams are developed in the far-source facies belt. Volcanoes of this period influenced the distribution of clastic reservoirs by the effusion facies and intrusive facies near conical craters. Water depth becomes deeper when the late Oligocene strata are deposited, thick-bed continuous underwater distributary channels and an estuary dam is developed in the sedimentary area. Volcanic activity was moderate until the last major eruption. During this period, the hydrothermal vent in the far-source facies belt is the main factor affecting the distribution of clastic reservoirs.

It is of great significance for the further fine description of reservoirs and regional exploration.
Expired Medications as Corrosion Inhibitors in the Oil and Gas Industry
Authors: Almubarak T. , AlOtaibi F. , Rafie M. , Baiz A.
Published: October 2023

As environmental awareness is rising worldwide, the oil and gas industry is introducing alternative chemicals in their operation that can degrade after disposal. Yet, there is a bigger concern regarding waste materials that are generated daily and accumulate in landfills with minimal recycling solutions. Research has shown that flushed expired medications leach pharmaceuticals into the environment. Consequently, causing severe harm to plants and aquatic life. This paper explores the possibility of utilizing expired high-use medications as corrosion inhibitors.

To determine the inhibition efficiency of expired medications, low carbon steel metal coupons were exposed to 15 wt.% HCl solutions at temperatures between 77-200°F. The medications have been divided into 3 categories based on their functionality: Category A, Category B, and Category C. Medications from each category were powdered and were used in these tests at a concentration of 2 wt.% for 6 hours. In addition, a control solution containing no corrosion inhibitor was used to establish a corrosion rate for a base case.

Category C medication was observed to perform well at room temperature providing a maximum of 99% corrosion inhibition efficiency. Category A and Category B on the other hand, did not provide as much corrosion inhibition. At a temperature of 150°F, the control solution showed a catastrophic failure producing a corrosion rate of 0.371 lb/ft2, whereas the use of Category C medication was observed to maintain good corrosion inhibition efficiency of 88.3%. When the temperature was raised to 200°F, the corrosion rate observed was 0. 0.0352 lb/ft2 for Category C medication, in the presence of 1 wt.% corrosion inhibitor intensifier. These results pass the oil and gas acceptable low carbon steel corrosion requirements of producing a corrosion rate below 0.05 lb/ft2 for the duration of 6 hours.

The work shows that expired medications can be utilized as corrosion inhibitors. Due to being expired and not fit for human consumption, the cost is inherently low. Thus, these chemicals may provide alternatives to commercial corrosion inhibitors while concurrently reducing damage to the environment.
Flow Profile Evaluation in Producer Wells by Geochemical Studies of Oil and Water and Analysis of Anomalies Associated with Deep Fault Zones
Authors: Shipaeva M. S. , Nurgaliev D. K. , Sudakov V. A. , Shakirov A. A. , Ganiev B. G. , Lutfullin A. A.
Published: October 2023

A major problem in the mature oil fields is the accompanying water production and oil production from different layers. Geochemical signals from different formations and sources can be used for identification flow profile. The study of geochemistry by area allows to establish the migration paths and movement of fluids inside the reservoir. This article focuses on the geochemical composition and isotopic geochemistry of brines and oils, as well as the metal content and the use of fingerprinting for oils (biomarker analysis). It allows to determine: the modes of development of reserves in different parts of the field, the distribution of liquid flows. The main tasks are: identification of geochemical anomalous zones and wells, analysis of the water source in return wells, analysis of communication between geochemical data and cumulative oil recovery. The first step involves selecting candidate wells for sampling. Then reservoir fluid samples are taken, and their unique composition is measured through high-precision mass spectrometric studies (ICP-MS), revealing the content of components to billions of fractions. The "oil fingerprinting" method (GC-MS) is used to identify biomarkers in oil composition and conditions of their origin. Using the developed automated algorithm allows identifying the distinctive characteristics of each reservoir and each phase - water and oil. Graphs and maps are plotted based on the distribution of the identified geoindicators. Geochemical survey was carried out by samples of wellhead samples of more than 100 wells, working for carbonate and terrigenous reservoirs. Area maps of changes in the geochemical background of the field have been constructed. The data of the fluid's geochemical composition from the development objects gave the determining of the inflow profile of each phase in the section of the perforated layers and allowed to compare it with the available geophysical field surveys. The identified difference of oils by the coefficient 2nC29/C28+C30 indicates different stages of hydrocarbons inflow into the traps. In the Devonian system the bright anomalies in the geochemical composition of water and oil were discovered, which are associated with faults and wells with record oil production for the last 50 years, where the actual cumulative production exceeds the volume of the originally estimated recoverable oil. Received data was used in the adaptation of the reservoir simulation model.
Applying Machine Learning NLP Algorithm for Reconciliation Geology and Petrophysics in Rock Typing
Authors: Tveritnev A. , Khanji M. , Abdullah S. , Rojas L. , Ermilov A. , Al Mansoori F. , Alblooshi A.
Published: October 2023

Oil- and gas-bearing rock deposits have distinct properties that significantly influence fluid distribution in pore spaces and the rock's ability to facilitate fluid flow. Rock typing involves analyzing various subsurface data to understand property relationships, enabling predictions even in data-limited areas. Central to this is understanding porosity, permeability, and saturation, which are crucial for identifying fluid types, volumes, flow rates, and estimating fluid recovery potential. These fundamental properties form the basis for informed decision-making in hydrocarbon reservoir development. While extensive descriptions with significant information exist, the data is frozen in text format and needs integration into analytical solutions like rock typing algorithms.

Applying text analysis, a crucial area in natural language processing, aims to extract meaningful insights and valuable information from unstructured textual data. With the vast amount of text generated every day, automated and efficient text analysis methods are becoming increasingly essential. Machine learning techniques have revolutionized the analysis and understanding of text data. In this paper, we present a comprehensive summary of the available methods for text analysis using machine learning, covering various stages of the process, from data preprocessing to advanced text modeling approaches. The overview explores the strengths and limitations of each method, providing researchers and practitioners with valuable insights for their text analysis endeavors.

A data-driven rock typing scheme is necessary for decision-making and optimization to achieve the best ultimate recovery of hydrocarbons in the most efficient way.
Conquer Liquid Loading in Raageshwari Gas Field by Automated Intermittent Production and Deliquification
Authors: Johri Nitin , Kadam Sanket , Veeken Kees , Prakash Aditya , Suvarna Hrithik , Singh Prakhar , Daukia Shashank , Kadirus Sandeep , Goswami Anindya , Aakash Suyash
Published: October 2023

The Raageshwari gas field is a tight, highly laminated retrograde gas condensate reservoir. The field is developed by multistage fracturing of wells with 3-1/2" and 4-1/2" monobore completions. Many wells have started liquid loading and are producing intermittent which reduces production capacity and restricts ultimate recovery. This paper presents efforts to date, first to manage intermittent production and second to restore stable production and increase ultimate recovery by means of deliquification.

After the onset of liquid loading, intermittent production is optimized by automating the production and shut-in periods. This allows time to evaluate, select and implement deliquification measures to delay well abandonment and maximize ultimate recovery. This paper describes the results of three deliquification techniques i.e. (1) Velocity String (VS), (2) Foam-Assisted Lift (FAL), and (3) Surface Gas Ejector.

Inflow performance is key to forecasting the incremental production associated with deliquification. With limited bottomhole data, surface production data was used to estimate both reservoir pressure and inflow resistance.
SmartVessel-v2: A Faster, Better, Stronger, Safety Monitoring Solution for Marine Vessels
Authors: Egorov D. , Sharan S. , Tahiri M. , Tamaazousti Y. , Amri M.
Published: October 2023

At ADIPEC'2022, SmartVessel, a vision-based HSE monitoring system, showed remarkable results in addressing HSE challenges in Marine Vessels. Despite its innovative features, SmartVessel was limited in its analysis of operational situation on working site as it relies solely on images, lacking temporal context. This deficiency leads to numerous false alarms and unnecessary operations interruptions. To address this issue, the new version of AI solution called SmartVessel-v2 was proposed. Despite the large number of advances, the main one can be called features tracking capabilities and temporal modeling. The brand-new version promises higher accuracy and efficiency, less false alarms and at higher running speed, increasing the safety of workers on-site.

The goal of this paper is to present the recent advances of previously presented AI based HSE surveillance system. The paper covers new safety related business cases introduced in the solution and corresponding novel algorithms to process and analyze them. It also highlights overall advances of AI pipeline helped to achieve higher level of accuracy and outstanding reduction in number of false alarms.

The last but not least, experience of solution large scale deployment for a whole fleet is described to share the knowledge about challenges, lessons learned and best practices how to handle this process in the optimal way. It can be extremely useful for all steps of design, development and deployment for any AI-based CCTV because it helps organize the process in correct way and avoid potential issues related to hardware and infrastructure, environmental, business and operational issues.
Re-Development of Tight Fractured Carbonates Through Extended Laterals and Hydraulic Fracturing
Authors: Buono A. , Taylor C. , Dordan A. , Evans B. , Staus G. , Zhu C. , MacQuaker J.
Published: October 2023

In this paper we compare development scenarios in a fractured carbonate play between historic vertical/short horizontal development and modern hydraulically fractured extended lateral development. The hydrocarbon production is analyzed and compared from fracture versus matrix play perspectives in this tight carbonate play. Here we are explicitly investigating the utility of applying unconventional technology to traditionally low/variably producing carbonate reservoirs as a means of increasing EUR and decreasing development scale variability. To meet this objective, we analyzed representative historical production data from a naturally fractured, fine-grained calcareous reservoir and compared it to production from the same unit where unconventional technology has been used to stimulate additional production from the matrix components. Due to its long production history and recent redevelopment efforts by industry, the Austin Chalk was chosen as a natural laboratory to test how recent artificial stimulation techniques lead to additional production from a wider range of pore systems.

We utilized petrophysical and microscopy data to compare rock attributes between the most common historic landing zone and the artificially stimulated zone, and determined the origin of the fluids produced from the stimulated zones. Additionally, we used production data from offset wells where different development strategies had been used as a method of comparing real world results as they relate to the study. The resulting data were then assessed in terms of matrix vs fracture delivery and zonal contributions to produced oils. We found that drainages of hydrocarbons produced from Austin Chalk landed wells ranged from Austin Chalk C Zone to the Eagle Ford/K64SB Zone; whereas hydrocarbons produced from Eagle Ford landed wells predominately drained the Eagle Ford/K64S Zone. These data reveal that utilizing unconventional technology to redevelop tight carbonate fields can lead to significant uplift in both well productivity and field life. This approach has the potential to be deployed in tight carbonate/fractured carbonate plays globally.
Sour Service Fracture Toughness from Lab-Scale to Full-Scale: An Overview of the Impact of Test Parameters and How They Link with the Cracking Mechanism
Authors: Thébault F. , Mizukami A. , Andres B. , Garcia D. , Gomes C. , Barsoum I.
Published: October 2023

Unconventional wells are well known to be cost driven and require cost-effective material due to the shorter production cycle after hydraulic fracking than conventional developments. As many of ADNOC gas discoveries are deep carbonate reservoirs and inherently sour, Sulfide Stress Cracking (SSC) risk must be considered during completion design. The integration of fracture mechanics into that process requires the determination of an accurate measure of the fracture toughness against SSC, e.g. KISSC, such that the risk of burst can be predicted and avoided more accurately in the field. This paper reminds the learnings from previous attempts for correlating burst pressure obtained in full-scale tests with fracture mechanics outputs from small-scale sour tests. The most used and relevant fracture mechanics tests employed on high strength OCTG steels in sour environments are described in a second part. A third part is dedicated to the review of the most important parameters affecting the measurement of the SSC fracture toughness. Followed a discussion on the reason why a crack arrest test like NACE TM0177 DCB test provides higher KISSC than a crack start test like a constant load SENT test.