NCG is increasingly being co-injected with steam in heavy oil production systems to reduce heat loss and greenhouse gas emissions, as well as to maintain reservoir pressure. Given increased use of NCG co-injection, the validity of conventional subcool models must be revisited since they assume that the steam chamber is comprised of water alone. The current study makes modifications to the pure-steam hydrostatic subcool model, as well as the Yuan & Nugent (2013) subcool model to account for the presence of NCG in the steam chamber. Using typical values from the Athabasca oilfield, the study then compares the liquid-height predictions made by the original and modified models and proposes rules-of-thumb that correct for the presence of NCG. In general, increasing NCG in the steam chamber results in a reduction in subcool relative to pure steam. According to modified hydrostatic model, to achieve a liquid-pool height equal to that of pure steam injection, the subcool must be increased by 0.60K per 1% increase in the vapor-phase molar fraction. In contrast, over a wide range of production rates and drawdowns, the modified Yuan & Nugent (2013) model predicts that to achieve a liquid-pool height equal to that of the pure steam case, the subcool must be increased by 0.66K per 1% increase in the vapor-phase molar fraction. Despite the rule-of-thumbs being qualitatively in line with expectations, they suffer from the inability to accurately calculate subcool from field data. The final section of the paper reviews limitations of subcool as a well performance metric and proposes an alternative method of assessment that relies on data that are more readily available to operators.
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Data-driven decision-making strategy for thermal well completion
Various wellbore completion strategies have been developed for thermal wells in Western Canada. The idea in this paper is estimating the improvement of oil production and steam injection if flow control devices (FCDs) will be installed for the next wells to be drilled, or if FCDs were installed at a particular well-pad that has not yet been completed with any FCDs. The approach is based on labeled real data for 68 well-pads from seven major thermal projects in Western Canada.
Three phases make up the paper’s methodology. The first phase compares wells with and without FCDs to evaluate the performance of the FCDs based on normalized oil production and cumulative steam oil ratio (cSOR). The second phase involves clustering well-pads using an unsupervised incremental-dynamic algorithm. An estimation of FCD contribution to enhancing oil production and cSOR is also performed for test well-pads based on their most similar cluster. In the third phase, cross-validation is employed to ensure that the estimation is trustworthy, and that the procedure is generalizable.
To evaluate the performance of FCDs, a reliable comparison was made using normalized oil production and cSOR. Based on our analysis from October 2002 to March 2022, successful FCD deployment resulted 42% more normalized oil and a 37% reduction in cSOR. Among these, liner deployed (LD) FCDs increased oil production by 44% while decreasing cSOR by 58%. Although tubing deployed (TD) FCDs are installed in problematic wells, they produced 40% more oil while decreasing cSOR by 21% in successful cases. Successful inflow control devices (ICDs) increased oil production by 40% while lowering cSOR by 45%. Successful outflow control devices (OCDs) increased oil production by 82% while reducing cSOR by 22%. The clustering algorithm separates the database into four clusters that will be utilized in the estimating phase. In the estimation phase, ten well-pads (15% of the database) are presumed to be new well-pads to be drilled (test data). Based on the estimation results, the root mean square errors (RMSEs) for FCDs contribution to enhancing oil production and cSOR for the test well-pads are 12%. Cross-validation was also performed to assess the approach’s predictability for new data, to verify that our technique is generalizable.
The findings indicate that FCDs might result in lower capital expenditures (CapEx) and greenhouse gas (GHG) emissions intensity for SAGD well-pad developments, allowing them to reduce emissions. The conclusions of this research will aid production engineers in their knowledge of relative production performance. The findings may be used to examine paradigm shifts in the development of heavy oil deposits as technology advances while keeping economic constraints in mind.
Passive flow control devices—well design and physics of their different flow regimes: A review
As wells shift towards producing or injecting along their entire length, frictional pressure losses and reservoir heterogeneities become larger issues in completion design. There is now general agreement that passive flow control devices (PFCDs) are effective in mitigating these issues. However, the interplay of PFCDs with the reservoir, as well as their fluid mechanics have been generally treated non-rigorously. Towards providing a more scientifically rigorous understanding of PFCDs, the current work presents the following through a survey of the literature:
The effects of frictional pressure loss and reservoir heterogeneity on wellbore performance through the lens of simplified reservoir flow equations, and how PFCDs modify these equations to combat these problems. 2. Flow theory relative to PFCDs; the significant dimensionless parameters within the different flow regimes; and PFCD performance data within the literature recast in terms of these dimensionless parameters. 3. Strategies for mitigating the erosion, corrosion and plugging of PFCDs. Broadly speaking, the review identifies that: 1. PFCDs alleviate the deleteriousness of frictional pressure loss and reservoir heterogeneity by either counteracting or overwhelming their effects. Studies recommend a PFCD flow resistance roughly equal to that of the reservoir or wellbore friction.
A hybrid GBPSO algorithm for permeability estimation using PSD and porosity
Particle size distribution measurements can be used for permeability estimation, and it is widely accepted that there exhibits a certain degree of correlation between permeability and porosity. In this paper, an efficient, low-cost, and reliable approach is used to develop an empirical correlation for estimating permeability based on particle size distribution characteristics and porosity in two modes: mode #1 includes 5% (D5), 10% (D10) and 60% (D60) of the cumulative passing particle size distribution curve and porosity for situations where porosity is known, and mode #2 where porosity is unknown. To optimize the coefficient of the proposed relationships, genetic-binary particle swarm optimization algorithm is used. A database consisting of 50 samples collected from four wells drilled in two neighboring pads in Western Canada were used, and their permeability values were predicted successfully. A validation based on a reference study and an application of sand completion design based on the finding of this study are also discussed. The novelties of the proposed approach are examining the effect of fines content, investigating the full range of particle size distribution curve, and using a hybrid intelligent method to optimize the coefficients of the correlations. In addition to sand completion deigns purposes, the proposed method can be used in enhanced oil recovery studies, reservoir management, and reservoir simulation applications.
The role of fouling materials strength on unplugging sand control devices using electrohydraulic stimulation
Previous studies showed that the fouling materials strongly affect the plugging of sand control devices during the oil production, thereby reducing oil productivity index drastically. In this study, we investigate how the compressive and tensile strengths of fouling materials affect the cleaning performance of shock waves generated by an electrohydraulic stimulation (EHS) tool.
First, we synthetically plug wire-wrapped screens using different class G cement slurries widely used in oil fields. Silica, calcite, clay, and organic carbon powder as additives are mixed with the cement at different concentrations. Next, we evaluate the compressive and tensile strengths of the cured cement samples by performing uniaxial compressive strength (UCS) and Brazilian tests. Finally, the cleaning performance of the EHS tool is evaluated for plugged wire-wrapped screens.
The UCS and Brazilian tests results show that the presence of additives changes the mechanical properties of cement samples. The compressive and tensile strengths of cement samples prepared with silica are found to be higher than those prepared with calcite and clay. Besides, the results of the pulsing stimulation treatment performed by the EHS tool show that the cleaning performance of the EHS tool for the wire-wrapped screens plugged with cement and carbon powder is the highest among all samples as cement samples with carbon powder represent the weakest mechanical properties (UCS and tensile strengths) among all samples. This study provides valuable insights into understanding the effect of shock waves on cleaning the plugged wire-wrapped screens. The results also enable production engineers to better plan for the treatment of damaged wells.
Data-driven well pad development performance review: Role of liner design
Steam Assisted Gravity Drainage (SAGD) is the dominant in-situ method for oil production in Western Canada. The current study analyzed the relative performance of various well-completion practices using data from 4,000 well pairs that were drilled over a decade. The data analysis provided a unique opportunity to find best operating practices. The scope of this paper is to review the performance of major thermal projects in Canada and investigating the effect of liner design and Flow Control Devices (FCDs) on well pair performance and development.
Cumulative oil production and cumulative steam oil ratio (cSOR) were used as the key metrics in comparing the well performance in a SAGD operation. However, to compare different pads and different projects, it was critical to normalize the data with geological variation, well length, well spacing, and with consideration to the well failure rate, remedial completion and re-drills. In this paper we review seven thermal projects of four key operators with almost 3,500 wells and 1,200 well pairs in operation as early as 1996. All geoscience, and production/injection data have been extracted from public databases and utilized to develop a data-driven model.
The reservoir thickness variation for each well was determined using available geoscience data, and through the development of a geological model based on the available core data and well logs. The model was used to define the drainage volume for each well pair, which in turn was used to assign a geological ranking to the well. The cumulative oil production and cSOR were then normalized with the geological ranking and the size of the net drainage volume. The number of well pairs in each pad and the cumulative pad production were normalized against the number of days in production and their relative decline, which allowed for comparison between pads within the same project, as well as pads from other projects. The cumulative production of the active pads in each project was used to compare the relative performance of different projects. Also, we separated the projects and wells based on their use of FCDs in the producer and injector to compare the relative performance of each technology in the field.
This paper is the initial phase of the study on the role of completion design on relative well and well pad performance. The results will help completion and production engineers to better understand the well pair and pad relative performance and how to normalize the oil production data against geological variation to compare performance.
Evaluation, Implementation, and Operations of an FCD for SAGD Producer Wells
The goal of this paper is to present the philosophies for the qualification and flow loop testing of FCD nozzles as well as the macroscopic implementation and operations of FCDs in SAGD producer wells. A quantitative methodology to evaluate FCD nozzles to choke back steam will be presented. Flow loop testing data will be shown to illustrate the qualification process. We will also discuss if sand control screens should be put on the tubing deployed inflow control devices. Some modeling and field examples will be shown. In the end, field data of the SAGD producer wells installed with the FCDs will be presented. Experience to manage and operate the wells will be shared.
An Investigation into Current Sand Control Testing Practices for Steam Assisted Gravity Drainage Production Wells
Sand control screens (SCD) have been widely installed in wells producing bitumen from unconsolidated formations. The screens are typically designed using general rules-of-thumb. The sand retention testing (SRT) technique has gained attention from the industry for the custom design and performance assessment of SCD. However, the success of SRT experimentation highly depends on the accuracy of the experimental design and variables. This work examines the impact of the setup design, sample preparation, near-wellbore stress conditions, fluid flow rates, and brine chemistry on the testing results and, accordingly, screen design. The SRT experiments were carried out using the replicated samples from the McMurray Formation at Long Lake Field. The results were compared with the test results on the original reservoir samples presented in the literature. Subsequently, a parametric study was performed by changing one testing parameter at a test, gradually making the conditions more comparable to the actual wellbore conditions. The results indicate that the fluid flow rate is the most influential parameter on sand production, followed by the packing technique, stress magnitude, and brine salinity level. The paper presents a workflow for the sand control testing procedure for designing the SCD in the steam-assisted gravity drainage (SAGD) operations.
A dual-directional flow control device for cyclic steam stimulation applications
Cyclic steam stimulation (CSS) is one the most effective thermal recovery methods. It is widely used as the primary thermal recovery method to recovery heavy oil fields in Middle East, Asia Pacific, North and South America. In this paper, a novel dual-directional flow control device (FCD) will be introduced. This FCD technology can allocate accurate steam outflow into the reservoir formation and improve steam quality during steam injection period and can mitigate steam breakthrough from the neighboring wells during production period.
In the first section, we will give a brief introduction on CSS and the main issues encountered in the field operation. A multi-directional flow control nozzle specifically designed for CSS application will be presented. Design philosophy in thermodynamics and hydrodynamics of the nozzle will be discussed in detail. Field performance results, Computational Fluid Dynamics (CFD) and flow loop testing data will be shown to evaluate the performance of the technology. The application of the technology in steam assisted thermal applications will be introduced. Well-known issues such as erosion and scaling on the FCD tools will be studied in the end.
An intelligent system for multi-label classification based on particle size and shape features
Intelligent systems are becoming more and more popular in the petroleum industry. Particle Size Distribution (PSD) based on sieve size is a key signature of the unconsolidated/weakly consolidated sandstone formations and is commonly the main parameter in the sand control design.
With available extensive PSD measurement techniques and a large number of measurements, especially for horizontal wells, it is necessary to classify the PSDs prior to further analysis for the sand control design. On the other hand, PSD analysis is not enough for sand control design, and particle shapes need to be taken into account as well. A successful clustering algorithm for the mentioned purposes needs to be a cascade, multi-label, unsupervised and self-adaptive approach since the particles can be assigned to more than one group and there is no prior idea on how many clusters should be formed after the clustering process. Besides, due to the differences between sieve size and shape features, they should be used separately for clustering the particles.
In the current study, a cascade approach is used for clustering the particles. In the first level of the cascade, an unsupervised and self-adaptive algorithm is introduced based on the sieve size features. The algorithm optimizes the number of clusters through a self-adaptive and incremental approach. The proposed clustering method uses a minimum similarity threshold (δ) as the only input parameter to start the clustering and tries to minimize the number of clusters during the clustering. In the second level of the cascade, the similarity between all particles in each cluster with their corresponding cluster-center is measured, and those particles that do not respect the δ in terms of the shape similarity, are moved out of the cluster.
The novelty of the proposed method is in three folds. The first one is to provide a particle clustering algorithm, which works based on the whole range of the sizes and shape descriptors rather than focusing on certain points in the size graph (D-values). The second one is the dynamic nature of the clustering, which tends to optimize the number of clusters during the clustering process. The third one is that we have used a cascade approach for involving both size and shape parameters for the clustering. Our proposed method can be applied in field application for downhole monitoring and sand screen design.