bluuebunny/crossref_metadata_2025 huggingface dataset:
Stability of Biopolymer and Partially Hydrolyzed Polyacrylamide in Presence of H2S and Oxygen
Authors: Al-Murayri Mohammed Taha , Kamal Dawood Sulaiman , Garcia Jose Gregorio , Al-Tameemi Naser , Driver Jonathan , Hernandez Richard , Fortenberry Robert , Britton Christopher
Published: October 2018

There are many oil reservoirs worldwide with substantial amount of H2S but otherwise very favorable conditions for polymer flooding such as low temperature, high permeability, and moderate to high oil viscosity. However, there is a legitimate concern about the chemical stability of polymers when there is dissolved oxygen in the injection water or injection facility and its high concentrations of H2S in the reservoir.

Several synthetic polymers and biopolymers were selected for stability testing under a wide range of conditions. We focused on identifying the concentration limits for co-presence of H2S and oxygen for which the synthetic and biopolymers are stable for an extended period, using different, widely available brine compositions. Experiments were conducted with and without standard polymer protection packages to evaluate their effects on stability and degradation under sour conditions. Viscosity of polymer solutions with varying concentrations of H2S and oxygen were measured and compared with the oxygen free or H2S free solution viscosities for a period of 6 months. Several methods of safely introducing H2S to the polymer solution were investigated and compared.

The laboratory results indicated that biopolymers were stable at all the concentrations of oxygen and H2S concentrations studied. Three synthetic polymers tested showed some degradation in the presence of oxygen and H2S but were stable when either species is absent. The results indicated that oxygen is the limiting reagent in the degradation reaction with partially hydrolyzed polyacrylamide (HPAM) polymers under normal reservoir conditions.

We observed little-to-no difference in degradation between samples with 10 or 100 ppm H2S at 500 ppb oxygen concentration, so H2S is not the limiting reagent under these conditions. Additionally, HPAM exposed to 10 ppm H2S and intermediate levels of oxygen (~0.5 ppm) only partially degrades, while samples exposed to H2S and ambient oxygen completely degrade. We anticipate these results will be useful for operators evaluating the potential of polymer flooding in sour reservoirs to follow a stricter polymer preparation at the surface facility to minimize oxygen concenration.
Peoples in Voluntary Isolation, Hydrocarbon Exploration and Recommended Practices – 10 Years After
Authors: Benalcazar Fernando L. , Thurber Mark W.
Published: October 2018

Objectives/Scope

A case study about the interaction and management of PVIs with E&P activities in the upper Amazon basin of Ecuador was presented in an SPE paper at Rio de Janeiro Conference in 2010. We outlined the history of PVIs within the context of E&P activities in remote tropical rainforest, and the actions taken by stakeholders to understand and protect these vulnerable groups. This paper will provide an evaluation of the strategies that have worked or failed in protecting the PVIs during the past 10 years since the publication of our original paper.

Methods, Procedures, Process

This paper will draw on our own personal experience in the Ecuadorian Amazon, as well as interviews and publications on the PVIs since 2010. We will update the timeline of events and link those to specific policies that have been implemented by the government of Ecuador, operators in the oil company concessions, and other stakeholders. Interviews will be conducted with key decision-makers in the government, community relations professionals in the oil industry, academics and non-profit organizations (NGOs); to map out the evolving story of the PVIs and their prospects for the future. Information will be geo-referenced in a GIS system to better understand location of encounters with PVI, and how those may relate to E&P and other activities.

Results, Observations, Conclusions

The PVIs continue survive in a NoGoZone (Area Intangible) that is surrounded and superimposed by oil company concessions. There has been increased E&P activity in the buffer zone of the NoGoZone during the past 10 years - including seismic exploration and drilling, road building, and construction of production facilities, which has resulted in additional conflicts, including violent clashes between oil workers, settlers and PVIs, resulting in injury and death. The government of Ecuador, as well as oil companies, have implemented some effective measures to prevent conflict, but with mixed success. Although there is some improvement in management of PVIs since 2010, the issue is generally left unattended by petroleum companies until there is a violent clash.

Novel/Additive Information

Proposals for specific solutions and more proactive stakeholder involvement and coordination will be presented, that need to be led by the oil companies and the government of Ecuador. It is hoped that this paper will generate more specific protective actions in Ecuador and in-depth discussions with SPE on how this complex issue should be managed worldwide by the O&G industry.
Determining Water Saturation in Permian Basin Intercalated Reservoirs Using NMR Log Data
Authors: Rojas Pedro A. , Bacciarelli Mark , Elkington Peter , Shokeir Ramez , Newsham Kent , Pumphrey Joe , Lopez Egleé , Morys Marian , Avdeev Dmitry
Published: October 2018

Alternating conventional and unconventional reservoir layers in the Permian Basin challenge the acquisition, processing, and interpretation of water saturation (Sw) using nuclear magnetic resonance (NMR) log data. A new-generation NMR wireline tool addresses these challenges using a specially designed conventional-unconventional activation sequence to enable construction of optimized maps of Longitudinal–Transversal Relaxation times (T1-T2 maps) at regular depth intervals.

T1-T2 maps are used to compute level-by-level Sw based on a multicomponent fluid model with appropriate statistical properties. Each spot in the T1-T2 space represents a fluid component from which a volume fraction is calculated. Integrating the volume fractions gives the total porosity. Because of the diverse relaxation mechanisms in the conventional and unconventional layers, oil spot positions with T1/T2 values greater than two reflect either viscosity (for bulk relaxation) or pore-size distribution (for surface/volume relaxation). Water tends to be close to the 1:1 T1/T2 diagonal line with T1/T2 values less than two. Low permeability means that mud-filtrate invasion does not appear on the T1-T2 maps.

NMR porosity matched expected values based on core and density-neutron log analysis. NMR fluid-typing-derived Sw—including clay bound water (CBW), capillary bound water (BVI), and free water—matched values from tested intervals. Results are in good agreement with reference values from production and core data within an uncertainty of one standard deviation. The resolution of fluid components in intervals where the components overlap can be enhanced by changes in the inversion parameters and map-grid dimensions.

This methodology for conventional-unconventional data acquisition followed by a multimodel approach for fluid typing will be applied to other wells. It enables a more accurate assessment of water saturation, especially when intercalated layers of conventional and unconventional reservoirs are present.
Effects of High Pressure on the Performance of Existing Two-Phase Flow Models in Wellbores
Authors: Daraboina Nagu , Chi Yuandao , Sarica Cem , Pereyra Eduardo , Scott Stuart L.
Published: October 2018

Multiphase flow is of vital importance to ensure the economic and safe transportation of unprocessed well streams from the reservoir to downstream process facilities. Several orders of magnitude higher pressures were experienced in the field compared to the near atmospheric laboratory conditions. In order to investigate the effect of high pressure on the two-phase flow and the performance of existing two-phase flow models, a systematic experimental study was conducted at high pressures (350, 550, 750 psig) in a vertical pipe. The positive frictional pressure gradient was observed and investigated under these high pressure conditions. In addition, statistical parameters were utilized to evaluate the model performance, and the uncertainties correlated with pressures were elucidated. It was found that most of the pressure gradient and liquid holdup data fall in the 20% error range.
Water Control Diagnostic Plot Pattern Recognition Using Support Vector Machine
Authors: Mukhanov Akhan , Arturo Garcia Carlos , Torres Henry
Published: October 2018

Petroleum engineers widely use Chan water control diagnostic plots to visually examine patterns for mechanisms behind excessive water production in petroleum wells. Distinct signatures reveal constant water-oil ratio (WOR), normal displacement of oil by water, multilayer channeling, and rapid channeling. Visual diagnosis requires extensive practical experience. High well counts amplify the need for timely relevant solutions. This study presents a supervised machine learning (ML) technique, support vector machine (SVM), to automatically identify Chan diagnostic patterns for timely detection and control of excess water production.

The project involved publicly available production data. First, we performed manual identification of different Chan plot patterns and split the data set for training, cross-validation, and testing. Next, we normalized each subset, balanced the number of samples per pattern, trained the SVM model, and evaluated its ability on the test data set. The final stage involved model parameter tuning to explore opportunities to improve the model accuracy.

When collecting representative samples, we observed uneven sample counts for pattern type subsets. Balancing the training data set was necessary to ensure that the model could generalize well for previously unseen production data. To ensure a relevant comparison among wells within each pattern type, we performed time- and WOR-based normalization.

We confirmed that the SVM model was highly accurate across diverse fields and hence did not exhibit a locality bias. Operator companies can harness the prior classification of water control trends by experienced engineers. As more wells start exhibiting specific pattern signatures, the algorithm helps to proactively identify them. The approach maximizes the effectiveness of water production analysis and helps to reinforce technical quality and continuity among engineering personnel.

The study demonstrated an application of SVM to the classification task of identifying water control diagnostic plot signatures across different fields. We proposed stricter visual definitions of signature types. Patterns such as normal displacement and multilayer channeling are extremely similar; therefore, we presented feature engineering required to increase classification accuracy in similar edge cases. With various kernels, the described SVM methodology can help production engineers to proactively perform surveillance activities that require identifying signature patterns in Chan plots.
Young Researcher Program: Developing Today's Innovators and Tomorrow's Leaders
Authors: Kokal Sunil
Published: October 2018

Is your education and training complete after you graduate from university? In today's competitive world, the answer is a resounding "no." Success in your career requires that you create a plan, take advantage of all the resources and opportunities to hone your skills, and continue to learn. That is part of the motivation for the development of the Young Researcher Program (YRP) at Saudi Aramco's Advanced Research Center (EXPEC ARC), the company's upstream research and development center.

The program was established with the objective of developing self-motivated and innovative researchers who lead in their area of specialty and support the company's vision, mission and strategic goals. It provides an opportunity for qualified engineers and geoscientists to become engineering/scientific specialists and, at the same time, provides the company with advanced technical expertise in the specialties for which there is a critical need. The program has a clear structure with distinct phases, and qualified candidates are matched with the most appropriate mentors. This strategy ensures that the young researchers obtain the required experience, further education and exposure for their chosen specialty. The program provides a roadmap for optimizing the professional growth and advancement of candidates. The program is sufficiently flexible to respond to candidates' training and work requirements, and enables them to achieve higher levels of competence and productivity. An important part of the program is the close relationship between the mentee and their mentor.

This paper will highlight the main features of the unique and successful program to develop young researchers. It will describe the program, roles and responsibilities of various entities, graduation requirements and its tracking and evaluation. It presents a success story that can be the basis for others to follow.
Wear Resistant, Friction Reducing Coatings Reduce Tubing Wear in Sucker Rod Couplings Application: Lab Testing and Field Trial Results
Authors: Jackson M. S. , Howell D. A. , Bailey J. R. , Rajagopalan S. , Ozekcin A. , Inglish G. , Allen C.
Published: October 2018

Two novel wear-resistant, low-friction coatings were evaluated on sucker rod couplings in both laboratory and field settings. Laboratory testing simulated cyclic downhole motion while applying a realistic side loading of 74 lbs. force to mimic conditions in which tubing wear typically occurs. Standard spray-metal couplings were compared with coated couplings to assess tubing and coupling wear after 450,000 cycles. Three wells with high tubing failure frequencies were selected as field candidates for the coated couplings to assess their impact on tubing failure frequency. The coupling placement in the rod string targeted known areas of high wear in the production tubing of each well.

Laboratory results showed that both coatings reduced tubing wear substantially when compared with the standard spray-metal couplings. Coating A reduced wear by a factor of 2X, and Coating B reduced wear by a factor of 6.6X, with the tubing still within drift ID after 450,000 cycles. During the lab tests, 0.0023 inches of material were removed from Coating A and 0.0001 inches was removed from Coating B. During field trials, Coating A increased the tubing life from an average of 5 to 20 (4X) months without failure in the two wells tested, at which point the field trial was ended. Coating B increased the tubing life from 6 to 19 (3.1X) months in the single sand producing well in which it was tested. Coating A was tested in a well with low sand concentration and Coating B was tested in a well with substantial sand present, showing that Coating B was able to perform in a more abrasive environment.

In summary, the described coatings drastically reduced tubing wear in the lab which also translated directly into a reduction in frequency of costly tubing repair workovers. This paper presents how novel wear-resistant friction-reducing coated couplings can improve performance of problematic sucker rod pump wells that experience a high frequency of tubing failures due to wear.
Main Aspects of the Integrated Asset Modeling and Gas Field Development Optimization under Surface Facilities Constraints
Authors: Mikhin Alexey , Salavatullin Karim , Kamartdinov Marat
Published: October 2018

The paper covers the Company's experience in Integrated Asset Modeling (IAM) through the example of gas-condensate Field Z. The problems arising at different stages of modeling were highlighted, revision of historical production data was performed, and optimization of field development was carried out by using IAM technology. Finally a comparison of simulation model production forecast (without taking into account surface facilities) with integrated model (with influence of surface facilities) was presented.
Adaptive Option in Geological Modeling of Petroleum Reservoirs
Authors: Taraskin Evgenii , Ursegov Stanislav , Taraskin Nikolay
Published: October 2018

The adaptive geological model differs from the deterministic one in that it takes into account the uncertainty of the initial data, has a degree of detail corresponding to the level of accuracy of the geological information, and reproduces the main regularities of the structure of the oil and gas object under consideration, primarily for the purpose of predicting its geology in undeveloped zones. At the first stage, adaptive geological models of separate layers identified by the results of detailed correlation of the considered object are constructed independently from each other, and then the single-layer models are summed up into a multilayer adaptive geological model of the object as a whole. With the adaptive approach, traditional methods of interpolation of geological and production data are not applied. The basis of adaptive geological modeling is the seismic data. The essence is that the seismic data vector is available both at the wells and at the points of the inter-well spacing, so any geological parameter can be calculated from this vector using a special fuzzy-logic function. At the same time, such function cannot be the same for the whole model polygon, so an additional so-called fuzzy-grid is developed. A grid with large cells, which contain local fuzzy-logic functions. Since fuzzy-logical functions are formed on the basis of geological and production information of the considered object, they can differ substantially for other objects. Thus, the mathematical apparatus of a geological model automatically modifies to the specific initial data, and therefore it is called adaptive. The calculated parameters of the adaptive geological model cells through which the wells pass are not necessarily the same as the actual well data. The reason is that these parameters are calculated using functions in which the initial data of neighboring wells participate. Deviations of calculated results from actual data characterize the degree of "defectiveness" of geological and production information. Thus, the adaptive geological model in comparison with the deterministic one gives a more meaningful result both about the geological structure of the considered object and the degree of reliability of its representation.
Integrating Downhole Temperature Sensing Datasets and Visual Analytics for Improved Gas Lift Well Surveillance
Authors: Bello Oladele , Bale Derek S. , Yang Lei , Yang Don , Kb Ajish , Lajith Murali , Lazarus Sony
Published: October 2018

Given the near ubiquity of fiber-optic, information and communication technologies in reservoir and well management, there is a significant need for one-stop shop downhole distributed sensing data analysis methods together with machine learning techniques towards autonomous analysis of such data sources. However, traditional approaches of converting distributed temperature sensor (DTS) data to actionable insights for optimizing gas lift well operations management remain dependent on training based on human annotations. Annotation of downhole distributed temperature sensor data is a laborious task that is not feasible in practice to train a big data classification algorithm for accurate and reliable anomaly detection of gas lift valves. Furthermore, even obtaining training examples for event diagnosis is challenging due to the rarity of some gas lift valve problems. In gas lift well surveillance, it is essential to generate real-time results to allow a swift response by an engineer to prevent harmful consequences of gas lift valve failure onsets on well performance. The online learning capabilities, also mean that the data classification model can be continuously updated to accommodate reservoir changes in the well environment. In this paper, we propose a novel online real-time DTS data visual analytics platform for gas lift wells using big data tools. The proposed system combines Apache Kafka for data ingestion, Apache Spark for in-memory data processing and analytics, Apache Cassandra for storing raw data and processed results, and INT geo toolkit for data visualization. Specifically, the data analytics pipeline uses data mining algorithms to statistically learn features from the DTS measurements. The learned features are used as inputs to a k-means algorithm and then use supervised learning to predict the performance status of gas lift valves and raise alarms based on analytics-based intelligent warning system. The performance of the proposed system architecture for detecting gas lift valve anomaly is evaluated under varying deployment scenarios. To the best of our knowledge, DTS data analytics pipeline system has not been used for real-time anomaly detection in gas lift well operations.
LEAN Mobile Production Facility to Unlock Marginal Oil Resources
Authors: Poopaiboon Tanthai , Supalasate Phruettiphan , Suebsook Jiranoot , Sakulkaew Sitanun , Surattanasunya Pawin , Eksaengsri Achapan , Charoensawadpong Panunya
Published: October 2018

This paper propose a LEAN design and LEAN approach for project development of Mobile Production Facility (MPF). The Mobile Production Facility (MPF) is the well known facility developed in onshore oil and gas field for mature field which the field development plan has extended to remote areas which contain small marginal oil prospects. The LEAN design for Mobile Production Facility could improve the economics of onshore oil and gas projects development by reducing capital expenditure (CAPEX) and project development lead times and increasing flexibility for production planning through the mobilization design, and be a key factor in the economic exploitation of both marginal and mature fields. Insight gained through in-house design, international code & standard, and package design experts led to the development of the LEAN Mobile Production Facility proposed in this paper. Discussion include a characteristic of a reference oilfield, project background, application of Mobile Production Facility, the innovative design of package and equipment leading to lower CAPEX in detail, as well as the benefits and limitations of the LEAN Mobile Production Facility. Areas of future project development in support of LEAN Mobile Production Facility are identified, including the potential to unlock the further marginal reserves.
Feasibility of Nitrogen Injection in a Multi-layered Lean Gas Condensate Reservoir
Authors: Canchucaja Ramiro , Sueiro Manuel
Published: October 2018

The main objective of this study is to demonstrate in a conceptual fashion the feasibility of change of field development strategy by the use of nitrogen injection in the most north-western section of a lean gas condensate reservoir located in the Peruvian jungle. A reservoir depletion strategy is being taking place since start-up in 2014. This new development is accomplished by turning a producer well into an injector and by installing new processing facilities for nitrogen separation and rejection. A drilling campaign for this new field development is avoided; a fact that places a considerable cost reduction of implementation especially in a location where an offshore-like field development strategy has been adopted.

Dynamic reservoir simulation requires a compositional model for reservoir simulation calculations owing to the nature of the gas condensate fluid that is being produced. Multiple contact miscibility takes place at the nitrogen front so that liquid dropout will be pervasive but in lower degree in one of the formations owing to the difference of composition. This fact is supported by calculations and fluid properties when pressure is even below dew point. A key aspect of nitrogen injection in this field is difference of rock properties between producing formations in a multi-layered reservoir. Therefore, sensitivity analysis is performed to optimize injection and liquid production by assessing well completion, injection flowrate, injection start-up and operational conditions of new surface facilities.
Aspects of the Development of Low-Permeability Gas Reservoirs of Turonian Age
Authors: Kiselyov Anton , Oshnyakov Igor , Melikov Ruslan , Samoilov Mikhail , Korolev Alexander , Loznyuk Oleg
Published: October 2018

Annotation. The article is devoted to the consideration of the prospects evaluation for commercial production of Turonian gas sediments. There are features of geological reserves estimate, field development issues, status of the pilot project the prospects of involving the reserves of the Turonian deposits in full-scale development at the Kharampur field reviewed.
Cloud-Based Solution for Advanced Real-Time Fracturing Evaluation
Authors: Parkhonyuk Sergey , Nikolaev Max , Fedorov Andrey , Konchenko Andrey , Vik Torbjoern
Published: October 2018

The ability to make real-time adjustments to hydraulic fracturing treatment design and pumping schedules leads to more-effective proppant placement and ensures every cluster delivers its full potential. There are numerous advanced methods to monitor and interpret the fracturing downhole events: microseismic analysis, distributed measurements with fiber optics, and high-frequency pressure monitoring. Advances in digital technologies allowed creating a cloud-based application combining downhole and surface data to enable real-time fracturing design adjustments from anywhere.

The application uses a public cloud solutions stack to synchronize surface and downhole measurements and visualize them on the Web. All computations are performed on virtual machines that create the visualization of downhole events in milliseconds. Interpretation of distributed temperature survey (DTS) and heterodyne distributed vibration sensing (hDVS) data has enabled reliable monitoring of diversion techniques, leak detection, and improvements in well integrity and provides support for any type of well intervention. The innovation in the use of the cloud-based application comes from the combination of a novel technique for processing and visualization of high-frequency pressure monitoring (HFPM). HFPM monitoring provides a cost-effective solution for completion efficiency.

The application is currently used for a novel wireline service that utilizes a fiber-optic cable for downhole temperature and acoustics measurements. Results have shown consistency and reliability in the interpretation of received data and confirmation of wellbore events, particularly in DTS and hDVS measurements. Field tests with HFPM have demonstrated that all processing and computations can be reasonably automated in a cloud to provide access to fracturing monitoring at anytime, from anywhere, and from any device. That provides excellent flexibility and means for further reducing the cost of well completions and maintenance, boosting the efficiency, and lowering cost per barrel. A technology stack of a secure public cloud makes an application cost effective and seamlessly scalable on demand. At the same time, the progress of the application does not stop with current possibilities. The innovation of cloud services, such as out-of-the-box machine learning libraries, is now available to for building applications on top of acquired data.

Cloud-based architecture is showing that any digital measurements can be effectively integrated, processed, and visualized in real time for decision making while the job is running. It creates a new service level for real-time fracturing monitoring that differentiates it from previous solutions.
Electrical Discharge Induced ESP Motor Bearing Failure
Authors: Ye Zheng , Wilcox Spencer
Published: October 2018

Motor bearings are a critical component in electric submersible pumping systems (ESP) motors. In many cases, dismantle analyses are unable to identify a definitive root cause for bearing failure. Several hypotheses have been studied to explain motor bearing failures. Some applications experience a higher bearing failure rate than other applications. In this paper, typical motor bearing failure modes will be reviewed, more specifically, the source of shaft voltage and the consequence of bearing electrical discharge failure will be discussed.

During bearing failure root-cause analysis, mechanical components have been the primary focus. Critical thermal expansion coefficients have been verified. The bearing running stress, temperature, eccentricity, film thickness, and lubrication flow have been simulated using cutting-edge finite element analysis (FEA) and computational fluid dynamics (CFD). Results show that in certain material combinations, the incompatibility of the thermal growth of bearing and sleeve material could reduce the running clearance, which would then increase the oil shear loss, and the bearing rubbing. However, tiny pitting has been found in the outside diameters (OD) of cracked bearings returned from the field, with more pitting found on the sleeve ODs. This evidence indicates another bearing failure mode: shaft-induced voltage and bearing electrical discharge.

The direct consequence of electrical discharge is generation of debris, vaporization of motor oil, quenching of bearing/sleeve surfaces, and increase in surface roughness. The debris size (0.001 in.) is larger than the hydrodynamic film thickness and can score the sleeve surfaces due to the loss of oil film protection. The chain of the motor bearing failure due to the electrical discharge is summarized, and this cannot be ruled out in other sizes, bearing systems, or material combinations in an ESP motor. By duplicating the poor power quality conditions, the pitting phenomenon on sleeve is confirmed. Future measurements have been planned to determine the correlation between the power quality and shaft voltage. This paper discusses the risk level for the bearing electrical discharge based the induced shaft voltage.

Electrical discharge bearing damage is a widespread problem that has been studied in other industries since 1992. Electrical discharge / shaft voltage problems can occur on any variable-speed drive motor. The source of electrical discharge through the bearing comes from the voltage potential building from the shaft to the ground (motor housing). However, ESP industries, which produce small motors with multiple rotor sections, have not conducted sufficient analysis to understand this problem. This paper fills the gap to discuss detailed indication evidence and analysis that can be used as a toolbox for motor bearing failure analysis for the ESP industry.
The Integrated Approach to Permeability Adjustment Based on the Simultaneous Well Log and Well Test Interpretation
Authors: Maksimova Elizaveta Nikitichna , Parfenov Nikita Andreevich , Belozerov Boris Vladimirovich
Published: October 2018

Nowadays, efficient field development cannot be imagined without the integrated interpretation of field data with different scale – core, well logs, and formation testers. The above mentioned methods allow definition of permeability values, which can be used during the geological and simulation modeling. However, it should be highlighted that there is no unified approach to permeability adjustment which may lead to unclear connections between absolute gas permeability (core, log) and effective permeability (well test) in reservoir models. As a result correct quantitative description of field development parameters could be questioned.

The present work considers the creation of the workflow for adjustment of core and therefore logs absolute permeability on field values, estimated from formation testing operations. It can be expected that the adjusted permeability values will describe the filtration process more correctly.

During the workflow creation the field with clastic deposits and special logging complex was analyzed. The permeability adjustment workflow, which consisted of several steps, was developed. First of all, absolute log permeability values were obtained taking types/facies into account. Then continuous log effective permeability curves were estimated based on the equations, derived during the analysis of PVT-properties and SCAL data. Finally, the comparison between log and well test permeability was performed.

It has been discovered that the developed methodology can be valid for clastic field with unconsolidated deposits. The transformation from average well test permeability to continuous log effective permeability was mathematically validated. Furthermore, it was shown that estimation of continuous fractional flow values can be performed for several intervals. Besides, calculated log mobility can be used for prediction of layers for which water filtration process can be faster.

The results, which were obtained during the workflow application, are planned to use during further simulation modeling. This can provide the improvement of development process prediction during the simulation modeling and future field development.
Distance-of-Investigation Could be Misused in Unconventional Heterogeneous Reservoirs with Non-Static Properties
Authors: Yuan Bin , Zhang Zhenzihao , Clarkson Christopher R.
Published: October 2018

The concept of distance-of-investigation (DOI) has been widely applied in rate- and pressure-transient analysis for estimating reservoir properties and for hydraulic fracture optimization. Despite its successful application in conventional reservoirs, significant errors arise when extending the concept to unconventional reservoirs. This work aims to clearly demonstrate such errors in the use of the traditional square-root-of-time model for DOI calculations in unconventional reservoirs, and to develop new models to improve the DOI calculations.

In this work, the following mechanisms in unconventional reservoirs are first incorporated into the calculation of DOI: 1) pressure-dependency of rock and fluid properties; 2) continuous/discontinuous spatial variation of reservoir properties. To achieve this, pseudo-pressure, pseudo-time and pseudo-distance are introduced to linearize the diffusivity equation. Two novel methods are developed for calculating DOI, one using the concept of continuous succession of steady-states, and the other using the concept of dynamic-drainage-area (DDA). Both models are verified using a series of fine-grid numerical simulations. A production data analysis workflow using the new DOI models is proposed to analytically characterize reservoir heterogeneity and fracture properties.

The new DOI models compensate for the inability of the traditional square-root-of-time model to capture spatial and temporal variations of reservoir and fluid properties. The pressure-dependency of fluids and reservoir (i.e., fluid density, viscosity, rock permeability and porosity) and reservoir heterogeneities (i.e., deterioration of reservoir quality from the primary fracture to the reservoir), can significantly retard the propagation of the DOI. Another important outcome of this work is to provide a practical and analytical approach to estimate the spatial heterogeneity directly from the production history of field cases.
Pore Volume Compressibility in Shale - Revisited
Authors: Davudov Davud , Moghanloo Rouzbeh Ghanbarnezhad , Lan Yuzheng
Published: October 2018

This study presents a novel method to estimated pore volume compressibility of shale samples based on mercury injection test data. We revisit our previous study (SPE-185059-PA) for more realistic estimation of pore volume compressibility for shale samples. We present a mathematical model to determine accessible porosity and pore compressibility as a function of pressure using Mercury Injection Capillary Pressure (MICP) data.

During MICP testing in a typical shale sample, the rock sample experiences conformance, compression, and intrusion stages as effective pressure increases. By evaluating compression stage, we calculate bulk compressibility. Further by introducing a system of equations, bulk compressibility is decomposed to estimate accessible pore and grain compressibility separately. Different from our previous model, in this study grain compressibility is calculated based on weight average of mineralogy determined from Fourier-transform infrared spectroscopy (FTIR) experiments. Moreover, bulk compressibility obtained from MICP data is compared with the values calculated from ultrasonic velocity measurements. Samples from both Haynesville shale plays are used to perform our study and validate the hypothesis.

Our results indicate that pore compressibility values are higher than anticipated, where calculated values are in the range of 1E-5 1/psi for shale samples at lower pressure. When pressure reaches to 8000 psi, pore compressibility reduces to the range of 1E-6 1/psi in most of the cases. Moreover, when compared with ultrasonic velocity measurements, results indicate that bulk compressibility obtained from MICP is overestimated at lower pressures and slightly underestimated at higher pressures.

The outcome of the paper changes the industry's take on prediction of the reservoir performance, especially the rock compaction mechanism. This study suggests that production owing to rock compaction can be much greater than what has often regarded, which can change the performance evaluation on a great number of reservoirs in terms of economic feasibility.
A Domain Decomposition Approach for Local Mesh Refinement in Space and Time
Authors: Singh Gurpreet , Wheeler Mary F.
Published: October 2018

Reservoir simulations for complex multiphase flow and transport problems often suffer from non-linear solver convergence issues. These manifest in the form of restrictively small time-step sizes even while using unconditionally stable fully implicit schemes. These problems are further compounded when a local mesh refinement is used to accurately represent reservoir parameters available such as permeability, porosity, etc., at multiple spatial scales. We discuss a domain decomposition approach that allows different time-step sizes and mesh refinements in different subdomains (Singh and Wheeler (2018)) of the reservoir that circumvents these issues without compromising computational efficiency and prediction accuracy. This approach extends the well-known methodology of local mesh refinement in space (Wheeler et al. (2002)) to time. Our numerical experiments indicate that non-linear solvers fail to converge, to the desired tolerance, due to large non-linear residuals in a smaller subdomain. We exploit this feature to identify subdomains where smaller time-step sizes are necessary while using large time-step sizes in the rest of the reservoir domain. The three key components of our approach are: (1) a space-time, enhanced velocity, domain decomposition approach that allows different mesh refinements and time-step sizes in different subdomains while preserving local mass conservation, (2) a residual based error estimator to identify or mark regions (or subdomains) that pose non-linear convergence issues, and (3) a fully coupled monolithic solver is also presented that solves the coarse and fine subdomain problems, both in space and time, simultaneously. This solution scheme is fully implicit and is therefore unconditionally stable. The results indicate that using large time-step sizes for the entire reservoir domain poses serious non-linear solver convergence issues. Although using a smaller time step size for the entire domain reduces the convergence issues, it also results in substantial computational overheads. The proposed space-time domain decomposition approach, with smaller time-step sizes in a subdomain and large time-step sizes everywhere else, circumvents the non-linear convergence issue without adding computational costs. Additionally, a space-time monolithic solver renders a massively parallel, time concurrent framework for solving flow and transport problems in subsurface porous media. Since the proposed approach is similar to the widely used finite difference scheme, it can be easily integrated in any existing legacy reservoir simulator.
Smart Oilfield Safety Net - An Intelligent System for Integrated Asset Integrity Management
Authors: Saeed Muhammad Rizwan , Chelmis Charalampos , Prasanna Viktor K.
Published: October 2018

In smart oilfields, a large volume of data is being generated related to assets, personnel, environment, and other production and business-related processes on a daily basis. Storing vast amounts of data is only justifiable if it leads to the discovery of actionable insights which can then be translated into improvements in operational efficiency and Health, Environment, and Safety (HES) conditions. Smart oilfield data is of high volume, variety, and velocity and can be located in multiple data silos. This presents an urgent need to develop scalable and extensible techniques that can enable domain experts to access data and perform analytics to yield better decisions and results. The focus of this paper is on the process of Asset Integrity Management and the role of Semantic Web technologies for significantly improving decision-making in this domain. The most significant challenges, thus, are to manage the high volumes of data, create a holistic view of asset integrity data, allow intuitive access to the data, and generate insights through an agile system that can be utilized by domain experts without requiring extensive assistance from IT experts. For this, we present the Smart Oil Field Safety Net (SOSNet) system, a Semantic Web-driven platform, that performs integration of asset integrity data, provides simplified querying mechanism for accessing the integrated data and facilitates analytics on top of it to improve efficiency and robustness of the process of Asset Integrity Management.
Robust Regression and Band Switching to Improve DAS Flow Estimates
Authors: Park Tim , Paleja Rakesh , Wojtaszek Magdalena
Published: October 2018

Within the Oil and Gas industry the use of Acoustics data for flow rate estimation is increasingly being explored. One technique is to consider the total spectral power of the signal within a specific frequency range, known as an FBE. The FBE, along with measured Flow rates, can then be used to build a simple regression model to estimate the flow rate. We collect acoustic data using Distributed Acoustic Sensing, DAS, and find that the recorded FBE generally contains some corrupted data and outliers. This may be due to well shut-in periods or other physical phenomena, or it may be due to issues in the DAS recording itself. These outliers can have a detrimental effect on the calibration of any predictive model and lead to biased flow predictions. We combat this by calibrating out model using Robust Regression techniques, such as Least Absolute Deviation, which are less influenced by outliers. Another practical concern is choosing the correct frequency band for the FBE. This can be done by evaluating the model performance on a training set, however we find that the signal quality within a band can diminish over time necessitating a change in the band used. Our challenge is to find a way to identify when a band is likely to be giving poor predictions. We do this by looking at the ratios between different FBE bands, we find that under normal conditions these are highly correlated, however for certain bands this correlation is lost over time. This can be used to determine when it is time to switch to use a different band. This paper contains the motivation and results of these techniques as they are applied to flow prediction in a gas producing well which has been part of a long-term flow monitoring project.
Big Data Approach for Geological Study of the Big Region West Siberia
Authors: Olneva Tatiana , Kuzmin Dmitryi , Rasskazova Svetlana , Timirgalin Azamat
Published: October 2018

Big Data technologies are now being actively integrated into the oil and gas sector owing to the need to improve operational efficiency and to optimize a variety of processes. Successful projects in data processing automation have already been implemented, for example, new breakthroughs are expected in digital field modelling projects /1/.

Geological and geophysical information accumulated over decades of studies in oil and gas bearing basins and fields development is a huge amount of data; Big Data approaches can be effectively applied to them, such as data mining, predictive analytics, training of a system on the reference objects. 3D seismic data is a classic example of Big Data. Their interpretation conventionally involves approaches based on Neural Networks, various classification and clustering algorithms /2/.

According to the experts, the West Siberian Petroleum Basin being a holistic system, has unique properties such as existence of giant and unique hydrocarbon accumulations /3/. The potential of the basin has not yet been determined. The authors focused their attention on the Achimov play. Applying the Big Data approach to a regional database may allow establishing new patterns in fields distribution and will contribute to the development of new unique exploration criteria.
Numerical Studies of Helium Distribution After Injection in the Gas Reservoir
Authors: Skriabina Anastasia
Published: October 2018

The paper presents the results of a multiparametric analysis of the helium saturation zone after its injection into a porous gas reservoir, the dynamics of its content in a withdrawn gas mixture and the helium recovery factor (target parameters). The calculations are performed on a three-dimensional composite hydrodynamic sector model of a homogeneous anisotropic reservoir of a virtual gas deposit. Based on the results obtained, the geological and technological factors are ranked according to the absolute value of the change of target parameters when the input parameters change. The dynamics of the influence of geological and technological factors on the target parameters is described concerning different withdrawn gas volume from the initial reserves. The identified relationships can be useful for planning of the experimental helium injection and the placement of exploitation wells at underground helium storage.
The Ultra-Expansion Completion Packer Integrated with Additive Manufacturing Technology
Authors: Deng Guijun , Kendall Alex , Wakefield John
Published: October 2018

The oil and gas industry has paid increasing attention to the momentum of Additive Manufacturing (AM) in the aerospace and autotmotive industries because this developing technology promises improved functionality, lead time reduction, and increased product reliability. AM technology eliminates traditional design limitations imposed by conventional manufacturing. Components and sub-assemblies with complex features and shapes can be manufactured where it was nearly impossible before, often with fewer components at a lower cost. This paper presents a completion packer designed for, and built with, AM with superior performance over the conventional product. A design topology optimization process is used to liberate engineers from shape complexity limitations and generate designs that target extreme performance goals. The AM raw material is subjected to rigorous mechanical characterization throughout the manufacturing process to ensure performance and reliability during a part's service life. Finally, test well validation is conducted to verify the design successfully meets all performance objectives.

An ultra-high expansion packer designed for multiple casing weights was developed in-house. The back-up ring system of this ultra-high expansion packer was additively manufactured. The novel AM design substantially reduces the number of components for the packer back-up system while remarkably boosting its expansion capacity and pressure rating. The packer element system installed with these AM backup rings offers extreme expansion ratio, truly zero extrusion gap, and superior conformability to as-rolled casing. Testing in-house showed: High diameter expansion ratio of 111% (over 50% improvement) with low setting force compared to existing packer design of the same size,Full pressure containment in at least 5 casing weights, and10,000 psi differential pressure held above, and then below, the packing element at 300°F.

This is the industry's first completion packer that utilizes Additive Manufacturing. It is of paramount importance since AM technology enables a faster time-to-market, enhanced performance, an optimized portfolio that reduces inventory, and an alternative means of cost reduction.