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Nicholson, A. Kirby (Pressure Diagnostics Ltd.) | Bachman, Robert C. (Pressure Diagnostics Ltd.) | Scherz, R. Yvonne (Endeavor Energy Resources) | Hawkes, Robert V. (Cordax Evaluation Technologies Inc.)
Abstract Pressure and stage volume are the least expensive and most readily available data for diagnostic analysis of hydraulic fracturing operations. Case history data from the Midland Basin is used to demonstrate how high-quality, time-synchronized pressure measurements at a treatment and an offsetting shut-in producing well can provide the necessary input to calculate fracture geometries at both wells and estimate perforation cluster efficiency at the treatment well. No special wellbore monitoring equipment is required. In summary, the methods outlined in this paper quantifies fracture geometries as compared to the more general observations of Daneshy (2020) and Haustveit et al. (2020). Pressures collected in Diagnostic Fracture Injection Tests (DFITs), select toe-stage full-scale fracture treatments, and offset observation wells are used to demonstrate a simple workflow. The pressure data combined with Volume to First Response (Vfr) at the observation well is used to create a geometry model of fracture length, width, and height estimates at the treatment well as illustrated in Figure 1. The producing fracture length of the observation well is also determined. Pressure Transient Analysis (PTA) techniques, a Perkins-Kern-Nordgren (PKN) fracture propagation model and offset well Fracture Driven Interaction (FDI) pressures are used to quantify hydraulic fracture dimensions. The PTA-derived Farfield Fracture Extension Pressure, FFEP, concept was introduced in Nicholson et al. (2019) and is summarized in Appendix B of this paper. FFEP replaces Instantaneous Shut-In Pressure, ISIP, for use in net pressure calculations. FFEP is determined and utilized in both DFITs and full-scale fracture inter-stage fall-off data. The use of the Primary Pressure Derivative (PPD) to accurately identify FFEP simplifies and speeds up the analysis, allowing for real time treatment decisions. This new technique is called Rapid-PTA. Additionally, the plotted shape and gradient of the observation-well pressure response can identify whether FDI's are hydraulic or poroelastic before a fracture stage is completed and may be used to change stage volume on the fly. Figure 1: Fracture Geometry Model with FDI Pressure Matching Case studies are presented showing the full workflow required to generate the fracture geometry model. The component inputs for the model are presented including a toe-stage DFIT, inter-stage pressure fall-off, and the FDI pressure build-up. We discuss how to optimize these hydraulic fractures in hindsight (look-back) and what might have been done in real time during the completion operations given this workflow and field-ready advanced data-handling capability. Hydraulic fracturing operations can be optimized in real time using new Rapid-PTA techniques for high quality pressure data collected on treating and observation wells. This process opens the door for more advanced geometry modeling and for rapid design changes to save costs and improve well productivity and ultimate recovery.
Zeinabady, Danial (University of Calgary) | Zanganeh, Behnam (University of Calgary, Chevron Canada Resources) | Shahamat, Sadeq (Birchcliff Energy Ltd.) | Clarkson, Christopher R. (University of Calgary)
Abstract The DFIT flowback analysis (DFIT-FBA) method, recently developed by the authors, is a new approach for obtaining minimum in-situ stress, reservoir pressure, and well productivity index estimates in a fraction of the time required by conventional DFITs. The goal of this study is to demonstrate the application of DFIT-FBA to hydraulic fracturing design and reservoir characterization by performing tests at multiple points along a horizontal well completed in an unconventional reservoir. Furthermore, new corrections are introduced to the DFIT-FBA method to account for perforation friction, tortuosity, and wellbore unloading during the flowback stage of the test. The time and cost efficiency associated with the DFIT-FBA method provides an opportunity to conduct multiple field tests without delaying the completion program. Several trials of the new method were performed for this study. These trials demonstrate application of the DFIT-FBA for testing multiple points along the lateral of a horizontal well (toe stage and additional clusters). The operational procedure for each DFIT-FBA test consists of two steps: 1) injection to initiate and propagate a mini hydraulic fracture and 2) flowback of the injected fluid on surface using a variable choke setting on the wellhead. Rate transient analysis methods are then applied to the flowback data to identify flow regimes and estimate closure and reservoir pressure. Flowing material balance analysis is used to estimate the well productivity index for studied reservoir intervals. Minimum in-situ stress, pore pressure and well productivity index estimates were successfully obtained for all the field trials and validated by comparison against a conventional DFIT. The new corrections for friction and wellbore unloading improved the accuracy of the closure and reservoir pressures by 4%. Furthermore, the results of flowing material balance analysis show that wellbore unloading might cause significant over-estimation of the well productivity index. Considerable variation in well productivity index was observed from the toe stage to the heel stage (along the lateral) for the studied well. This variation has significant implications for hydraulic fracture design optimization, particularly treatment pressures and volumes.
Abstract Fracture growth in layered formations with depth-dependent properties has been a topic of interest amongst researchers because of its critical influence on well performance. This paper revisits some of the existing height-growth models and discusses the evaluation process of a new and modified model developed after incorporating additional constraints.The net-pressure is the primary driver behind fracture propagation and the pressure distribution in the fracture plays an important role in vertical propagation, as it supplies the necessary energy for fracture advancement in the presence of opposing forces. The workflow adopted for this study included developing a preliminary model that solves a system of non-linear equations iteratively to arrive at fracture height versus net pressure mapping. The theoretical results were then compared to those available in the literature. The solution set was then extended to a 100-layer model after incorporating additional constraints using superposition techniques.The predicted outcomes were finally compared to the fracture height observations made in the field on several treatments. A reasonable agreement between model-predicted and observed height was observed when a comparison between the two was made, for most cases.The majority of these treatments were pumped in vertical wells, at low injection rates of up to 8.0 bbl/min (0.021 m/s) where net pressures were intentionally restricted to 250 psi (1.72 MPa) in order to prevent fracture rotation to the horizontal plane.The leak-off was minimal given the low permeability formations. In some cases, however, the pumping parameters and fluid imparted pressure distribution appeared to dominate. Overall, it was apparent that for a slowly advancing fracture front, which is the case in low injection rate treatments, the fracture height could be predicted with reasonable accuracy. This condition could also be met in high rate treatments pumped down multiple perforation clusters such as in horizontal wells, though fracture-height measurement may not be as straightforward as in vertical wells. The model developed under the current study is suitable for vertical wells where fracture treatments are pumped at low injection rates. The solid-mechanics solution that is presented here is independent of pumping parameters and can be readily implemented to assist in selection of critical design parameters prior to the job, with a wide range of applicability worldwide.
Abstract Economic optimization of a reservoir can be extremely tedious and time consuming. It is particularly difficult with many wells, some of which can become non-economic within the simulated time period. These problems can be mitigated by: 1) analyzing the results of a simulation once it has run, or 2) applying injection or production constraints at the well level. An example of option 1 would be integration with a spreadsheet or economic simulation package after the simulation has run. An example of option 2 would be to set a maximum water cut, upon which the well constraints could be changed, or the well could be shut in within the simulation. Both of these methods have drawbacks. If the goal is to account for how changes in a well operating strategy affects other wells, then analysis after the fact requires many runs to sequentially identify and modify well constraints at the correct times and in the correct order. In contrast, applying injection and production constraints to wells is not the same as applying true economic constraints. The objective of this work was to develop an automated method which includes economic considerations within the simulator to decrease the amount of time optimizing a single model and allows more time to analyze uncertainty within the economic decision making process. This study developed automated methods and procedures to include economic calculations within the context of a standard reservoir simulation. The method utilized modifications to available conditional logic features to internally include and export key economic metrics to support appropriate automatic field development changes. This method was tested using synthetic models with different amounts of wells and operating conditions. It was validated using after the fact calculations on a well by well basis to confirm the process. People costs are always among the most significant associated with running a business. Therefore, it is imperative for people to be as efficient and productive as possible. The method presented in this study significantly reduces the amount of time and effort associated with tedious and manual manipulations of simulation models. These savings enable an organization to focus on more value-added activities including, but not limited to, accurately optimizing and estimating of uncertainty associated decisions supported by reservoir simulation.
Alkinani, Husam Hasan (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb Tuama (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology)
Abstract Lost circulation and problems related to drilling present a major challenge for the drilling industry. Each year, billions are spent to treat these problems. There is not a single solution to lost circulation because of the complexity and kind of formations susceptible to this issue. Lost circulation treatment data for the Shuaiba formation (induced fractured formation) were gathered from drilled wells in Southern Iraq (over 2000). Treatments have been grouped according to the volume of mud loss as complete, severe, and partial loss remedies. Detailed costs and probabilities calculations were conducted. The costs of three types of loss treatments (partial, severe, and complete) were handled separately since some treatments of severe, and all treatments of complete losses have to be introducing through open end drill pipe (OEDP). Expected monetary value (EMV) and decision tree analysis (DTA) were utilized to choose the optimal mud loss pathway to treat the lost circulation type. In this study, probability and cost were both considered to select the practical and efficient strategy of stopping mud loss. Too many of the remedy scenarios were investigated. The selection of the optimum strategy for every type of loss was based on the lowest EMV and efficiency. Once both conditions were satisfied, the treatment strategies were selected to treat each type of loss. Treatment strategies were provided for complete, severe, and partial losses as flowcharts that can be utilized as a reference in the field to stop or at least mitigate this troublesome problem. The methods used in this paper have the possibility to be adopted and invested to treat mud loss based on historical data of treatments in any formation worldwide.
Karpaya, Shaturrvetan (PETRONAS Carigali Sdn.Bhd.) | Sidek, Sulaiman (PETRONAS Carigali Sdn.Bhd.) | Ab Ghani, Dani Angga (PETRONAS Carigali Sdn.Bhd.) | Ab Rahman, Hazrina (PETRONAS Carigali Sdn.Bhd.) | Yong, Aivin (KROHNE EMAS Sdn.Bhd.) | Subbarayan, Venukumaran (KROHNE EMAS Sdn.Bhd.) | Chew, Simon (Petrotechnical Inspection (M) Sdn.Bhd.)
Abstract Installation of Wet Gas Metering System (WGMS) on a platform for the purposes of real-time measurement of liquid and gas production rates as well as performance monitoring as part of reservoir and production optimization management are quite common nowadays in Malaysia. Nonetheless, understanding of wells production deliverability invariably measured using these Wet Gas Meter (WGM) which provides the notion of production rates contributed by the wells are paramount important, eventually the produced fluids will be processed by various surface equipment at the central processing platform before being transport to onshore facilities. However, the traditional WGM are known to operate within ±10% accuracy, whereby the confidence level on measurement of the produced fluids can be improved either by updating with accurate PVT flash table or combination of results from performing tracer dilution technique for data verification. Sarawak Gas Field contains a number of gas fields offshore East Malaysia, predominantly are carbonate type formation, where one (1) of the field operated by PETRONAS Carigali Sdn.Bhd.(PCSB) is a high temperature accumulation at which temperature at the Gas Water Contact (GWC) approximately 185°C and full wellstream Flowing Tubing Head Temperature (FTHT) records at 157°C. Cumulative field production of five (5) wells readings from WGM had shown 9.1% differences as compared to the export meter gas readings. As part of a strategy to provide maximum operational flexibility, improvement on accuracy of the WGM is required given that the wells have higher Technical Potential (TP) but are limited by threshold of the multi-stage surface processing capacity. This also impacts commerciality of the field to regaining the cost of capital investment and generate additional revenue especially when there is a surge in network gas demand, as the field unable to swiftly ramp-up its production to fulfill higher gas demand considering the reported production figures from cumulative WGM surpassing the surface equipment Safe Operating Envelope (SOE). Our approach begins with mass balance check at the WGMS and export meter including the fuel, flare and Produced Water Discharge (PWD) to check mass conservation by phases because regardless different type of phases change occurs at topside the total mass should be conserved (i.e. for total phases of gas, condensate and water) provided that precise measurement by the metering equipment. Tracer dilution measurement of gas, condensate and water flowrates were used to verify the latest calibrated Water Gas Ratio (WGR) and Condensate Gas Ratio (CGR) readings input into the WGM. Consequently, PVT separator samples were also taken via mini-separator for compositional analysis (both gas and condensate) and for mathematical recombination at the multi-rates CGR readings to generate a representative PVT compositional table. Simultaneously, process model simulation run was conducted using full wellstream PVT input to validate total field production at the export point. This paper presents practical approach to balance the account, to ensure the SOE at topside as well as to improve the PVT composition at the WGM for high temperature field that emphasizes on understanding of compositional variations across production network causing significant differences in total field production between WGM and the allocation meter.
Abstract The concept of minimum economic field size (MEFS) has been used by explorationists for almost four decades. MEFS is often the only filter to distinguish between a commercial and a non-commercial discovery—far before a wildcat well is drilled—to test a prospect for a working petroleum systems hypothesis. As simple as it gets, the concept started to lose traction in the 21 century as subsurface targets became more and more challenging. In the case of tight hydrocarbons, it is fairly common to observe a P90 case net present value (NPV) to be negative, a P50 case to be positive, and a P10 case to be negative again. The reason for this outcome is that a whole set of full-cycle factors, in addition to the field size, affects prospect commerciality. Their uncertainty ranges can match or exceed resource estimate uncertainty. These factors include, but are not limited to, initial productivity of development wells, estimated eltimate recovery (EUR) per well, decline curve parameters, capital investments, operating costs, and the project phases’ durations. A new way of handling the full universe of risks and uncertainties faced by modern explorers is already available in the new generation of industry-leading integrated prospect risk, resource and value assessment software. Innovators and thought leaders can already substitute MEFS with a commerciality threshold (CT) that neatly mimics board considerations at the final investment decision (FID) stage gate. Others can consider the economic chance of success (ECOS) estimated with a probabilistic full-cycle mindset, as an additional metric valuable for risk management purposes. Using fictional case studies inspired by real-life assessment situations, we discuss the additional value creation by a CT-powered workflow as compared to an MEFS-based one and explain the reasons for the key differences. The discussed workflow does not eliminate nature-specific uncertainties; neither does it reduce the geological risk. However, it helps to better understand human-controlled risks and prepare management exploration decisions with a greater degree of confidence.
Abstract In the greenfield development process, one of the key questions that needs to be answered is, "What is the range of EUR for a particular development concept and the associated completion method based on the existing range of subsurface uncertainties?" The key challenge then is how can the team forecast a representative range of EUR efficiently to obtain a range of results that represent a probabilistic outcome. During the reservoir modelling process of this case study, a total of 405 static realizations had been run and then a STOIIP S-curve was generated. In the next step, 20 cases each of "High, Mid and Low" static models were selected based on the S-curve distribution for the next phase of dynamic simulation due to time and resources constraint. In terms of completion, the same development concept and completion method is assumed, where each dynamic case requires 8 horizontal producing wells with 200 metres of completion interval. Wells placement aside, each of the 60 dynamic models should not have the same fixed perforation depths and intervals due to the geological uncertainties with regards to facies distribution and they need to be selected based on the well effective k-h and hydrocarbon saturation along each well trajectory. Manual work could be used to analyse the best intervals for each of the planned wells, or in this case, this laborious process was replaced with an automated selection of the optimum completion interval workflow using Python script. This paper will show the workflow of how a scripted Python code is designed to provide an "automated moving window" to find the best intervals along a well trajectory. This workflow was executed in the pre-processor of the dynamic simulator which has a workflow window with Python-embedded capability. The Python code then generated the simulation keyword COMPDATMD, which contained the best perforation intervals for all the wells as an output. This automated workflow resulted in an optimization of the completion intervals in all the 60 dynamic model cases, while the ultimate recovery for this greenfield development in Peninsula Malaysia increased by 30% compared to EUR from previously "unoptimized runs". This approach is managed to cut down the run preparation time by at least two weeks compared to the manual solution. The improved range of EUR is also considered as a more representative outcome of the field development evaluation. Utilizing emerging technology breakthrough such as ability to customize specific features via a programming language is important towards a successful era of the Fourth Industrial Revolution (4IR). The results of this automated and customized workflow automation demonstrate a successful application of using machine learning for enhanced problem-solving in reservoir simulation.
Abstract Depleted Fracture Gradients have been a challenge for the oil and gas industry during drilling and cementing operations for over 30 years. Yet, year after year, problems related to lost circulation, borehole instability (low mud weight due a low fracture gradient), and losses during cementing operations leading to NPT and remedial work continue to rank as some of the top NPT events that companies face. This paper will demonstrate how the geomechanical modeling, well execution and remedial strengthening operations should be implemented to provide for a successful outcome. The use of a Fracture Gradient (FG) framework will be discussed, and the use of a negotiated fracture gradient will highlight how the fracture gradient can be changed during operations. This paper will also show actual examples from Deepwater operations that have successfully executed a detailed borehole strengthening program. Through our offset studies and operational experience, we will provide a format for navigating complex depleted drilling issues and show an example on recovering from low fracture gradients. This paper will demonstrate (1) how our framework facilitated multi-disciplinary collaborative discussion among our subsurface and well engineering communities; (2) how the impacts of drilling fluids and operational procedures can change this lost circulation threshold; and (3) how our negotiated FG approach has successfully delivered wells drilled in narrow margins.
Jiang, Tongwen (PetroChina Exploration & Production Company, CNPC) | Zhou, Daiyu (PetroChina Tarim Oilfield Company, CNPC) | Wu, Yiming (PetroChina Tarim Oilfield Company, CNPC) | Chang, Lunjie (PetroChina Tarim Oilfield Company, CNPC) | Lian, Liming (RIPED, PetroChina, CNPC) | Wu, Zangyuan (PetroChina Tarim Oilfield Company, CNPC) | Zhou, Wei (RIPED, PetroChina, CNPC) | Fan, Kun (PetroChina Tarim Oilfield Company, CNPC) | Tang, Yongliang (PetroChina Tarim Oilfield Company, CNPC) | Yu, Hongwei (RIPED, PetroChina, CNPC) | Bian, Wanjiang (PetroChina Tarim Oilfield Company, CNPC) | Shao, Guangqiang (PetroChina Tarim Oilfield Company, CNPC) | Fan, Jiawei (PetroChina Tarim Oilfield Company, CNPC) | Wu, Lin (PetroChina Tarim Oilfield Company, CNPC) | Huang, Lan (PetroChina Tarim Oilfield Company, CNPC) | Kuang, Xiyu (PetroChina Tarim Oilfield Company, CNPC) | Fan, Jin (PetroChina Tarim Oilfield Company, CNPC) | Li, Yang (PetroChina Tarim Oilfield Company, CNPC)
Abstract This paper provide improved phase behavior models, trying to mitigate the problem that phase behavior of gas-crude system is difficult to describe in L block with low permeability and high water cut in China. This situation leads to a series of problems in CO2 flooding process and lower recovery up to expectations. The models is evaluated to possess both high calculation speed and accuracy compared with existing others. Characteristics of CO2-crude systems had been considered into repulsion-attraction type EOS (equation of state) based on the analysis of repulsion parameter and attraction parameter in EOS, and the improved EOS had been applied in developing calculation method of MMP (minimum miscible pressure). No ideality of CO2-crude systems had been considered into mixing rules of CO2-crude systems based on analysis of mixing rules of repulsion-attraction type EOS. Promotion had also been put into the obtain methods of parameters in phase behavior, including density, viscosity, MMP, critical parameters of plus components etc. All these methods are applied in L Block. The phase behavior models of CO2-crudes system promoted in this paper mainly include EOS, mixing rule and viscosity model and have been applied in CO2 flooding process in T Reservoir. The relative error of density calculation is reduced from 7% ∼ 20% to less than 1%and the modified EOS is applied to predict the MMP of the CO2-crude systems from 8 different blocks in T reservoir. The modified EOS also works well for the relative error of MMP prediction is reduced from 20% ∼ 70% to less than 5%. Compared with the existing mixing rules, the modified mixing rule is with higher calculation speed and accuracy. The relative error of components mole fraction calculation is reduced from 30% ∼ 80% to less than 10%. Compared with the existing viscosity models, there are large improvements of the modified viscosity model in accuracy. The relative error of viscosity simulation is reduced from more than 50% to about 5%. According to the simulation results, C2∼C15 are the key hydrocarbons with positive effect on the miscibility of CO2-crude systems, while C16+ are the key hydrocarbons with negative effect. The recovery of the pilot has increased by 23% by these methods. The improved phase behavior models provided in this paper possess as good performance as existing models in calculation speed, and accustom a big step forward in simulation accuracy. The modified components of the models also partially complete physical meaning in describing phase behavior of CO2-crude system. All the models mentioned above are finally applied in L block with HP/HT and high water cut and obtained an increase in recovery by 19.2%.