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Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
Abstract Uniformity of proppant distribution among multiple perforation clusters affects treatment efficiency in multistage fractured wells stimulated using the plug-and-perf technique. Multiple physical phenomena taking place in the well and perforation tunnels can cause uneven proppant distribution among multiple clusters. The problem has been studied in the recent years with experimental and computational fluid dynamics (CFD) methods, which provide useful insights but are impractical for routine designs. Simplified models that incorporated the proppant transport efficiency (PTE) correlation derived from the CFD results in a hydraulic fracture model have been also presented in literature. In this paper, we present a numerical model that simulates the transient proppant slurry flow in the wellbore, considering proppant transport and settling including bed formation, rate- and concentration-dependent pressure drop, PTE, and dynamic pressure coupling with the hydraulic fractures. The model is efficient and is designed to be an independent wellbore transport model so it can be integrated with any fracture models, including fully 3D and/or complex fracture network models, for practical design optimization. The model predictions are compared and found to agree with previously published studies. Parametric studies demonstrate sensitivity of proppant distribution to grain size, fluid viscosity, and pumping rate for fixed perforation designs. Analysis of the simulation results shows that the dominant cause of uneven proppant distribution is proppant inertia. Possible slurry stratification is less important, except for the cases with relatively low flow rates and near toe clusters. Accordingly, proppant distribution is less sensitive to perforation phasing than to the number of perforations in clusters. Alterations of the number of perforations per cluster within a stage enable achieving more even proppant distribution.
Abstract Coiled tubing (CT) integrity is critical for well intervention operations in the field. To monitor and manage tubing integrity, the industry has developed a number of computer models over the past decades. Among them, low-cycle fatigue (LCF) modeling plays a paramount role in safeguarding tubing integrity. LCF modeling of CT strings dates back to the 1980s. Recently, novel algorithms have contributed to developments in physics-based modeling of tubing fatigue and plasticity. As CT trips into and out of the well, it goes through bending-straightening cycles under high differential pressure. Such tough conditions lead to low- or ultralow-cycle fatigue, limiting CT useful life. The model proposed in this study is derived from a previous one and based on rigorously derived material parameters to compute the evolution of state variables from a wide range of loading conditions. Through newly formulated plasticity and strain parameters, a physics-based damage model predicts CT fatigue life, along with diametral growth and wall thinning. The revised modeling approach gives results for CT damage accumulation, diametral growth, and wall thinning under realistic field conditions, with experimental validation. For 20 different coiled tubing alloys, it was observed that the model improved in accuracy overall by about 18.8% and consistency by 14.0%, for constant pressure data sets of more than 4,500 data points. The modeling results provide insights into the nonlinear nature of fatigue damage accumulation. This study allowed developing recommendations to guide future analytical modeling and experimental investigations, to summarize theoretical findings in physics-based LCF modeling, and to provide practical guidelines for CT string management in the field. The study provides a fundamental understanding of CT LCF and introduces novel algorithms in plasticity and damage.
Abstract The wellbore and formation temperature environment around a system of multiple wells in close proximity is complex. Temperature simulation and prediction for a single isolated well is simplified by axisymmetric assumptions. Realistic multi-well environments do not have obvious symmetry and are interactive given different operating states including possibly a mix of producer versus injector wells. A simulation model of thermal interaction between closely spaced wells has been developed in a collaborative project. A large-scale validation of the model is presented here. An important field application is presented for a subsea well template where movement tolerances must be tightly controlled. Large-scale validation was conducted for an offshore platform development where more than 30 wells were drilled and brought onto production over a period of 4-5 years. As each well was drilled and completed, temperature logs where recorded which thereby gave a digital signature of the complex thermal environment below mudline as it evolved over time. The simulation model temperature for each well was corroborated against well temperature logs. A simultaneous boundary-condition of flowing wellhead temperatures and pressures for each well was compared against the model predictions. Also, a detailed predictive case study is presented for a 6 well subsea template. Model temperatures were used to assess the impact of cement height on wellhead movement within the template structure which featured lockdowns and tight tolerances on allowable movement within the housing profile. Predicted temperatures from the multi-well model agree closely with logs and correlate closely with characteristic temperature excursions from geothermal below the mudline down to the well path kick-off zone. Since the logs occur over time and account for a changing well population, the model is shown to accurately capture the time evolution of the complex temperature environment. The model explains unusual temperature log signatures as the result of sidetracks and the radial extent of heat affected zones from the parent wellbore. The subsea case study highlights the importance of predicting the complex multi-well temperature environment by demonstrating its impact on the wellhead movement given the uncertainty of cement tops for deeper shoes of combined conductor/surface casings. This learning informs subsea template design and selection with port options for cement grout and top-up jobs. Although the multi-well temperature model has been presented previously along with some field data validation, the large-scale study presented provides further and significant model validation. Extensive data over time and corroboration with unusual temperature log phenomena demonstrate model accuracy. The utilization of the model in the design and specification of a subsea template development provides a real-world example and demonstrates practical application as well as its usefulness.
Dindoruk, Birol (University of Houston (Previously at Shell International Exploration and Production Inc.)) | Ratnakar, Ram R. (Shell International Exploration and Production Inc.) | Suchismita, Sanyal (Shell India Markets Private Ltd.)
Summary We present thermodynamic modeling and pH measurements of fluid systems containing acid-gases (e.g., CO2 and H2S), water, and hydrocarbons—replicating the production and shutdown conditions in sour fields—for the purpose of evaluating top-of-line corrosion (TLC) and wellbore integrity and screening/selection of the proper wellbore materials. In particular: An equation of state (EOS) model using Peng-Robinson EOS in combination with the Huron-Vidal (HV) mixing rule for an aqueous subsystem is developed. In the model, subject EOS parameters are calibrated against existing thermodynamic data (saturation data for pure components and solubility data for binary systems) in literature. New in-situ pH measurement data are presented for a model system corresponding to a sour field. It was found that the wellbore can be subjected to pH levels as low as 2.7 with reservoir fluid containing 12 mol% CO2 and 88 mol% CH4 with downhole flowing conditions of 200 bar and 150°C and wellhead shut-in conditions of 300 bar and 4°C, as observed from the experiments. A modeling workflow is developed to estimate pH of the condensed water as a function of temperature and composition of the aqueous phase. The comparison between prediction and experimental measurement shows a very good match between the two (within pH ±0.1). Such studies (pH measurements and prediction) are not available in the literature but play important roles in material screening and assuring wellbore integrity for sour fields. More importantly, sensitivity analysis can be performed to investigate the effects of various factors (such as reservoir temperature/pressure, shutdown conditions, and compositions or extent of souring) on pH prediction. Furthermore, the methodologies developed through this work can also be extended to reservoir facilities, pipelines, sour gas disposal/handling units, and downstream systems such as water utilities, reactor plants, and refineries. The work can also support regulation/licensing for these sour systems.
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199561, “Validation of Transient Annular Pressure Buildup (APB) Model Predictions With Field Measurements in an Offshore Well and Characterization of Uncertainty Bounds,” by Rahul Pai, Anamika Gupta, and Udaya B. Sathuvalli, Blade Energy Partners, et al., prepared for the 2020 IADC/SPE International Drilling Conference and Exhibition, Galveston, Texas, 3-5 March. The paper has not been peer reviewed. The average geothermal gradient in the subject deepwater field in Nigeria is 4.37°C/100 m, nearly twice the gradient in most fields. As a result, the magnitude of the expected annular pressure buildup (APB) during steady-state production is large enough to threaten well integrity. Therefore, an insulating packer fluid (IPF) was used in Annulus A to reduce heat transfer to the outer annuli and to regulate the APB within acceptable values. The complete paper reports the results of a study that compares the temperature and pressure measurements from these wells with model predictions. Introduction Though APB has been studied by well designers for decades, the use of downhole measurements to study APB has been somewhat limited. Previous uses of downhole instrumentation to study APB phenomena principally have centered on monitoring the magnitude of the APB and managing the risk. None, as far as the authors are aware, use the results gathered from downhole measurements to verify the results of the models that routinely are used in the design of the wellbore tubulars and APB-mitigation technologies. Notwithstanding the wealth of literature on the subject of APB, several crucial and fundamental questions remain unanswered. Chief among these are: What is the accuracy of thermal-model temperature predictions during various well operations? How do temperature uncertainties influence APB predictions? When APB magnitudes are large enough to require installation of APB mitigation devices? How do the mitigation devices perform over the life of the well? The complete paper seeks to address these questions through an examination of downhole pressure and temperature measurements and a parallel analysis of model predictions. Furthermore, field data and model predictions are juxtaposed, sources of uncertainties in the measurement data and model inputs are considered, and overall uncertainties in the APB predictions (i.e., model estimates) are characterized.
Li, Bodong (EXPEC Advanced Research Center, Saudi Aramco) | Dokhani, Vahid (Yu Technolgoies Inc) | Zhan, Guodong David (EXPEC Advanced Research Center, Saudi Aramco) | Sehsah, Ossama (Drilling Technical Department, Saudi Aramco)
Critical decision making requires accurate downhole data to determine proper action for drilling operation. Using cost-effective drilling microchips to collect near real-time temperature distribution in the wellbore is valuable to accurately predict control parameters such as drilling fluid rheology and density under in-situ conditions. This study presents an iterative method to calibrate microchip measurements with depth. The accuracy of a transient thermal model to simulate the measured temperature profile is also investigated.
Multiple sets of microchips were deployed into two wells, a vertical and an inclined well, to describe the dynamic temperature distribution along the wellbores. The retrieved data from drilling microchips are compiled and processed. An iterative algorithm is developed to calibrate the microchips time-scale to depth considering slippage of microchips in drillpipe and annulus. An in-house transient thermal model is modified to predict the variation of wellbore temperature during microchips circulation.
It is shown that the true velocity of tracers in each interval depends on the flow regime and the rheological properties of drilling fluid. Comparing the predicted arrival times of tracers with the actual arrival times conclude that the maximum fluid velocity in each interval shall be used for calibration of tracers' data. The study concludes that the prediction of the transient model differs from the measured temperature profile for downhole intervals in early times. The discrepancy can be attributed to unknown prior temperature distribution in the wellbore, inaccurate thermal properties of the drilling fluid, and inaccurate empirical correlations.
This new integrated measurement and analysis method can be used as a primary input for well planning, cementing design and a diagnostic tool for potential problems such as lost circulation. This study provides new insights about the temperature distribution along the wellbore and elaborates on the necessity to address the transient processes in wellbores particularly during startups in deepwater drilling.
Electrical system design in capital projects takes place very early in the cycle because large motors and gas powered generators are long lead time items and plant assets require power during installation. This means that electrical design employs only preliminary process design data and instead relies on simple load factor formulas. Under-designing the electrical system could mean the process cannot reach nameplate capacity, which could have significant financial consequences. If a similar process unit has already been built, an accurate simulation of that process could be used to right-size the electrical system, especially if the process simulation is connected to an equally accurate electrical simulation. This would allow engineers to evaluate process and electrical dynamics to ensure electrical power always meets process demand and that the electrical design is adequate for a variety of real life scenarios, such as plant startup and shutdown, process upsets, and unplanned grid outages.
This paper explores the potential cost savings during a capital project and into the operational phase, the significant challenges in creating an accurate process simulation, and other use cases for a mixed process and electrical simulator can provide. A simple study was performed for a client where both the electrical design data and the process simulator was available to determine if the simulator was accurate enough to calculate load demand and if the motors were oversized in the unit. The crude unit was selected because it contained the largest number of medium voltage motors and was relatively easy to operate. The model and the historian predicted that the motors were oversized between 15–63%. Extrapolating the excess power to cost could reach 1.3 MUSD per year.
Dindoruk, Birol (Shell International Exploration and production Inc. & University of Houston) | Ratnakar, Ram R. (Shell International Exploration and production Inc) | Suchismita, Sanyal (Shell India Markets Private Ltd)
We present thermodynamic modeling and pH measurements of fluid systems containing acid-gases (e.g. CO2 and H2S), water and hydrocarbons – replicating the production and shutdown conditions in sour fields – for the purpose of evaluating top-of-line corrosion and wellbore integrity, and screening/selection of the proper wellbore materials. In particular:
An EOS model using Peng-Robinson EOS in combination with Huron-Vidal mixing rule for aqueous sub-system is developed. In the model, subject EOS parameters are calibrated against existing thermodynamic data (saturation data for pure components and solubility data for binary systems) in literature. A new in-situ pH measurement data is presented for a model system corresponding to sour field. It was found that the wellbore can be subjected to pH levels as low as 2.7 with reservoir fluid containing 12 mol% CO2 and 88 mol% methane with downhole flowing conditions of 200 bar and 150°C, and wellhead shut-in conditions of 300 bar and 4°C, as observed from the experiments. A modeling workflow is developed to estimate pH of the condensed water as a function of temperature and composition of the aqueous phase. The comparison between prediction and experimental measurement show very good match between the two (within pH ±0.1).
An EOS model using Peng-Robinson EOS in combination with Huron-Vidal mixing rule for aqueous sub-system is developed. In the model, subject EOS parameters are calibrated against existing thermodynamic data (saturation data for pure components and solubility data for binary systems) in literature.
A new in-situ pH measurement data is presented for a model system corresponding to sour field. It was found that the wellbore can be subjected to pH levels as low as 2.7 with reservoir fluid containing 12 mol% CO2 and 88 mol% methane with downhole flowing conditions of 200 bar and 150°C, and wellhead shut-in conditions of 300 bar and 4°C, as observed from the experiments.
A modeling workflow is developed to estimate pH of the condensed water as a function of temperature and composition of the aqueous phase. The comparison between prediction and experimental measurement show very good match between the two (within pH ±0.1).
Such studies (pH measurements and prediction) are not available in literature but play important role in material screening and assuring wellbore integrity for sour fields. More importantly, sensitivity analysis can be performed to investigate the effects of various factors (such as reservoir temperature/pressure, shutdown conditions, and compositions or extent of souring) on pH prediction. Furthermore, the methodologies developed through this work can also be extended to reservoir facilities, pipelines, sour gas disposal/handling units, as well as, downstream systems such as as water-utilities, reactor plants and refineries. The work can also support for regulation/licensing for these sour systems.
Summary A novel experimental and theoretical study on slug dissipation in a horizontal enlarged impacting tee‐junction (EIT) is carried out. Both flowing‐slug injection and stationary‐slug injection into the EIT are studied, and the effects of inlet slug length and liquid‐phase fluid properties on the slug dissipation in the EIT are investigated. A total of 161 experimental data are acquired for air‐water and air‐oil flow. The flowing‐slug data (with a horizontal inlet) show that the slug dissipation length increases with increasing mixture velocity, demonstrating a nonlinear trend with a steeper slope at lower mixture velocities. The effect of superficial gas velocity on the slug dissipation length is more pronounced compared with the effect of superficial liquid velocity. For stationary‐slug injection into the EIT (with a 5° upward inclined inlet), the injected slug lengths vary between 40d to 100d (d is the inlet diameter). The data reveal that, when increasing the superficial gas velocity or the inlet slug size, the dissipation length in the EIT branches increases. For this case, the ratio of the slug dissipation length to the inlet slug length is higher for air‐water compared with air‐oil. A slug dissipation model is developed using the slug‐tracking approach, which is based on the flow mechanisms of liquid shedding at the back of the slug and liquid drainage and penetration of bubble turning at the front of the slug. These phenomena result in different translational velocities at the back and the front of the slug, which result in the dissipation of the slug body. Evaluation of model predictions against the acquired experimental data shows an average absolute relative error of less than 11%.