|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Abstract Characterization of hydraulic fracture system in multi-fractured horizontal wells (MFHW) is one of the key steps in well spacing optimization of tight and shale reservoirs. Different methods have been proposed in the industry including core-through, micro-seismic, off-set pressure data monitoring during hydraulic fracturing, pressure depletion mapping, rate-transient analysis, pressure-transient analysis, and pressure interference test. Pressure interference test for a production and monitoring well pair includes flowing the production well at a stable rate while keeping the monitoring well shut-in and recording its pressure. In this study, the coupled flow of gas in hydraulic fractures and matrix systems during pressure interference test is modeled using an analytical method. The model is based on Laplace transform combined with pseudo-pressure and pseudo-time. The model is validated against numerical simulation to make sure the inter-well communication test is reasonably represented. Two key parameters were introduced and calculated with time using the analytical model including pressure drawdown ratio and pressure decline ratio. The model is applied to two field cases from Montney formation. In this case, two wells in the gas condensate region of Montney were selected for a pressure interference test. The monitoring well was equipped with downhole gauges. As the producing well was opened for production, the bottom-hole pressure of the monitoring well started declining at much lower rate than the production well. The pressure decline rate in the monitoring well eventually approached that of the producing well after days of production. This whole process was modeled using the analytical model of this study by adjusting the conductivity of the communicating fractures between the well pairs. This study provides a practical analytical tool for quantitative analysis of the interference test in MFHWs. This model can be integrated with other tools for improved characterization of hydraulic fracture systems in tight and shale reservoirs.
Hampton, Thomas J. (Consultant) | El-Mandouh, Mohamed (Consultant) | Weber, Stevan (Consultant) | Thaker, Tirth (Computer Modelling Group) | Patel, K.. (Computer Modelling Group) | Macaul, Barclay (Computer Modelling Group) | Erdle, Jim (Computer Modelling Group)
Abstract Mathematical Models are needed to aid in defining, analyzing, and quantifying solutions to design and manage steam floods. This paper discusses two main modeling methods – analytical and numerical simulation. Decisions as to which method to use and when to use them, requires an understanding of assumptions used, strengths, and limitations of each method. This paper presents advantages and disadvantages through comparison of analytical vs simulation when reservoir characterization becomes progressively more complex (dip, layering, heterogeneity between injector/producer, and reservoir thickness).While there are many analytical models, three analytical models are used for this paper:Marx & Langenheim, Modified Neuman, and Jeff Jones.The simulator used was CMG Stars on single pattern on both 5 Spot and 9 Spot patterns and Case 6 of 9 patterns, 5-Spot. Results were obtained using 6 different cases of varying reservoir properties based on Marx & Langenheim, Modified Neuman, and Jeff Jones models.Simulation was also done on each of the 6 cases, using Modified Neuman steam rates and then on Jeff Jones Steam rates using 9-Spot and 5-Spot patterns.This was done on predictive basis on inputs provided, without adjusting or history matching on analog or historical performance.Optimization runs using Particle Swarm Optimization was applied on one case in minimizing SOR and maximize NPV. Conclusion from comparing cases is that simulation is needed for complex geology, heterogeneity, and changes in layering. Also, simulation can be used for maximizing economics using AI based optimization tool. While understanding limitations, the analytical models are good for quick looks such as screening, scoping design, some surveillance, and for conceptual understanding of basic steam flood on uniform geologic properties. This paper is innovative in comparison of analytical models and simulation modeling.Results that quantify differences of oil rate, SOR, and injection rates (Neuman and Jeff Jones) impact on recovery factors is presented.
Abstract Multistage hydraulic fracturing is the common stimulation technique for shale formations. The treatment design, formation in-situ stress, and reservoir heterogeneity govern the fracture network propagation. Different techniques have been used to evaluate the fracture geometry and the completion efficiency including Chemical Tracers, Microseismic, Fiber Optics, and Production Logs. Most of these methods are post-fracture as well as time and cost intensive processes. The current study presents the use of fall-off data during and after stage fracturing to characterize producing surface area, permeability, and fracture conductivity. Shut-in data (15-30 minutes) was collected after each stage was completed. The fall-off data was processed first to remove the noise and water hammer effects. Log-Log derivative diagnostic plots were used to define the flow regime and the data were then matched with an analytical model to calculate producing surface area, permeability, and fracture conductivity. Diagnostic plots showed a unique signature of flow regimes. A long period of a spherical flow regime with negative half-slope was observed as an indication for limited entry flow either vertically or horizontally. A positive half-slope derivative represents a linear flow regime in an infinitely conductive tensile fracture. The quarter-slope derivative was observed in a bilinear flow regime that represents a finite conductivity fracture system. An extended radial flow regime was observed with zero slope derivative which represents a highly shear fractured network around the wellbore. For a long fall-off period, formation recharge may appear with a slope between unit and 1.5 slopes derivative, especially in over-pressured dry gas reservoirs. Analyzing fall-off data after stages are completed provides a free and real-time investigation method to estimate the fracture geometry and a measure of completion efficiency. Knowing the stage properties allows the reservoir engineer to build a simulation model to forecast the well performance and improve the well spacing.
Marine mining initiatives open a new field of subsea operations. Offshore oil and gas sites are still located primarily in areas where divers can support maintenance and repair requirements, but future marine mining will take place in greater depths and with a complexity of machines that requires support from robotic systems equipped with a substantial amount of artificial intelligence (AI). Technologies are being developed that have the potential to support marine mining in all stages from prospection to decommissioning. These developments will likely have substantial influence in the oil and gas industry, itself searching for ways to maximize exploitation of assets. Commercial off-the-shelf AUVs rely mostly on acoustic and inertial sensors for their navigation.
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 198586, “A New Continuous Waterflood Operations Optimization for a Mature Oil Field by Use of Analytical Work Flows That Improve Reservoir Characterization,” by Atul Yadav and Anton Malkov, SPE, Wintershall, and Essam Omara, Suez Oil Company, et al., prepared for the 2019 SPE Gas and Oil Technology Showcase and Conference, Dubai, 21–23 October. The paper has not been peer reviewed. In the complete paper, the authors present a novel approach that uses data-mining techniques on operations data of a complex mature oil field in the Gulf of Suez that is currently being waterflooded. Evidence is presented about how salinity data can be used to further justify the linkages between different wells obtained from cross-correlation analysis. The results presented in this research can be adapted to any waterflooded field to optimize recovery at frequent intervals where injection and production data are available continuously. Introduction Mature oil fields typically present challenges of increased water production and water handling. Considering the geological complexity and associated field-performance behavior, reservoir characterization to optimize water flooding is a major challenge. An integrated reservoir study was con ducted to minimize reservoir uncertainties and increase understanding of the field’s performance behavior. The acceptable history-matched model was used to estimate remaining oil potential, maintain and increase current production levels, and optimize the water-injection rate. Generally, history-matched models need to be updated throughout the life of producing fields as new subsurface data are acquired. Such integrated reservoir modeling studies, however, can be time-consuming and do not necessarily enable quicker decision-making around operational activities. The continuous recording of production and injection data presents new opportunities to apply novel analytical techniques to understand interwell connectivity in the reservoir. The current ability to store and analyze data, coupled with advances in the ability to interpret big data sets, has helped create an independent toolkit that provides analysis without the geological model. In addition, geological information such as pre-existing faults and the commingled or disconnected nature of production between different layers can be integrated to obtain and improve analyses from the analytical models. The authors analyze the results using Pearson’s cross-correlation analysis measure to obtain a qualitative analysis of the field. They also apply Spearman’s rank correlation analysis for the discussed field (henceforth named GOS for purposes of this paper) that helps compare injection and production data. The objective is to present a comparison between the analytical and the stream-lined approach to show consistency in reservoir characterization. The effective injector/producer pairs identified form an important component of the field development.
This paper describes the acquisition and interpretation of long-term pressure-buildup data in a plugged and abandoned deepwater appraisal well. To accomplish the test objectives at an acceptable cost, a novel combination of well testing, wireless-gauge technology, and material-balance techniques was used to allow the collection and interpretation of reservoir-pressure data over a planned period of 6 to 15 months following the well test. The final buildup duration was 428 days (14 months). Three interpretation methods of increasing complexity were used to provide insights into the reservoir. First, material balance was used to produce an estimate of the minimum connected reservoir volume.
Decline-curve analysis (DCA) is arguably the most commonly used method for forecasting reserves in unconventional reservoirs. Production data from several US unconventional plays are analyzed, and production forecasting is carried out with the traditional Arps methods as a basis for comparison. The results are compared with analytical models developed for each play to determine the suitability of each DCA method. At the most fundamental level, DCA involves fitting an empirical model of the trend in production decline from a well's history and projecting the trend into the future to determine the well's economic life and forecast cumulative production. The Arps decline model is established from the empirical observation that the loss ratio (the rate of change of the reciprocal of the instantaneous decline rate) is constant with time.
Multistage horizontal well completion with multiple short perforation clusters is a widely used method to maximize formation contact in unconventional reservoirs. However, a significant percentage of clusters are often not effectively stimulated. While some efforts have been made to improve completion efficiency, an expert with Schlumberger said that the industry still lacks an understanding of the fracture initiation process in a completion configuration with multiple clusters of spiral perforations. Until then, the expert said operators will not be able to quantitatively predict and assess completion efficiency. In a presentation held by the SPE Gulf Coast Section's Completions and Production Study Group, Xiaowei Weng discussed Schlumberger's development of a near-wellbore fracture initiation calculator based on an analytical elastic solution for cased and perforated completions.
Summary The objective of this study is to develop a new method that leads to diagnostic charts that quantify the pressure response between two interfering wells. Analytical linear flow models for single hydraulic fracture are used to develop a fracture hit model, which is next verified with a numerical model for validity. An analytical two‐fracture model is then developed to simulate flowing bottomhole pressure (BHP) of a shut‐in well, which interferes with the other well through a fracture hit, during well‐testing for a short‐term period. From the insight of two‐fracture analytical model, a dimensionless pressure scalar, which is proportional to square root of time, is proposed to summarize the interference level between two wells. Utilizing such proportionality between the defined dimensionless pressure scalar and square root of time, a diagnostic chart for quick assessment of the production interference level between wells is developed. Such diagnostic chart is also applied to interference caused by multifracture hits that a multistage fractured horizontal well with history match performed from the Eagle Ford formation is considered as a parent well for production interference quantification. A new identical horizontal well, which is just fractured but is not in production, is assumed parallel to the pre‐existing well. The result shows that when the percentage of fracture connection increases, the slope of dimensionless pressure scalar vs. square root of time increases proportionally to the percentage of fracture connection. Because the slope of dimensionless pressure scalar vs. square root of time is between 0 and 1, it can be used to quantify the well production interference level under different situations.
Summary This study focuses on the development of an analytical model to predict the long-term productivity of channel-fractured shale gas/oil wells. The accuracy was verified by comparing productivity calculated by the proposed model with numerical results. Sensitivity analysis was conducted to analyze significant parameters on the performance of channel fracturing. Field application of the model was conducted using production data obtained from an Eagle Ford Formation dry gas well, which was completed using channel fracturing. The procedure for estimating reservoir and stimulation parameters from production data was provided. The results indicated that the equivalent fracture width obtained from our model is consistent with the inversion of cubic law. Comparison with numerical simulations demonstrated that the proposed model might under- or overestimate well productivity, with mean absolute percentage error (MAPE) values of less than 8%. Sensitivity analysis indicated that, with the increase of fracture width, fracture half-length, and matrix permeability, the productivity of channel-fractured wells increases disproportionately. In addition, well productivity will increase as the ratio of the pillar radius to the length of channel fracture decreases, provided that the proppant pillars are stable and the fracture width is held constant. Under the conditions of smaller fracture width and larger matrix permeability, the effect of using channel fracturing to increase well productivity is more significant. However, as the fracture width becomes large, the benefits of channel fracturing will diminish. The case study indicated that the shale gas productivity estimated by the proposed model matches well with field data, with MAPE and R of 12.90% and 0.93, respectively. The proposed model provides a basis for optimizing the design of channel fracturing.