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Abstract Distributed Fiber Optics (DFO) technology has been the new face for unconventional well diagnostics. This technology focuses on measuring Distributed Acoustic Sensing (DAS) and Distrusted Temperature Sensing (DTS) to give an in-depth understanding of well productivity pre and post stimulation. Many different completion design strategies, both on surface and downhole, are used to obtain the best fracture network outcome; however, with complex geological features, different fracture designs, and fracture driven interactions (FDIs) effecting nearby wells, it is difficult to grasp a full understanding on completion design performance for each well. Validating completion designs and improving on the learnings found in each data set should be the foundation in developing each field. Capturing a data set with strong evidence of what works and what doesn't, can help the operator make better engineering decisions to make more efficient wells as well as help gauge the spacing between each well. The focus of this paper will be on a few case studies in the Bakken which vividly show how infill wells greatly interfered with production output. A DFO deployed with a 0.6" OD, 23,000-foot-long carbon fiber rod to acquire DAS and DTS for post frac flow, completion, and interference evaluation. This paper will dive into the DFO measurements taken post frac to further explain what effects are seen on completion designs caused by interferences with infill wells; the learnings taken from the DFO post frac were applied to further escalate the understanding and awareness of how infill wells will preform on future pad sites. A showcase of three separate data sets from the Bakken will identify how effective DFO technology can be in evaluating and making informed decisions on future frac completions. In this paper we will also show and discuss how DFO can measure real time FDI events and what measures can be taken to lessen the impact on negative interference caused by infill wells.
Abstract With a recent trend in increased infill well development in the Midland basin and other unconventional plays, it has been shown that depletion has a significant impact on hydraulic fracture propagation. This is largely because production drawdown causes in-situ stress changes, resulting in asymmetric fracture growth toward the depleted regions. In turn, this can have a negative impact on production capacity. For the initial part of this study, an infill child well was drilled and completed adjacent to a parent well that had been producing for two years. Due to drilling difficulties, the child well was steered to a new target zone located 125 feet above the original target. However, relative to the original target, treatment data from the new zone indicated abnormal treatment responses leading to a study to evaluate the source of these variations and subsequent mitigation. The initial study was conducted using a pore pressure estimation derived from drill bit geomechanics data to investigate depletion effects on the infill child well. The pore pressure results were compared to the child well treatment responses and bottom hole pressure measurements in the parent well. Following the initial study, additional hydraulic fracture modeling studies were conducted on a separate pad to investigate depletion around the infill wells, determine optimal well spacing for future wells given the level of depletion, and optimize treatment designs for future wells in similar depletion scenarios. A depletion model workflow was implemented based on integrating hydraulic fracture modeling and reservoir analytics for future infill pad development. The geomechanical properties were calibrated by DFIT results and pressure matching of the parent well treatments for the in-situ virgin conditions. Parent well fracture geometries were used in an RTA for an analytical approach of estimating drainage area of the parent wells. These were then applied to a depletion profile in the hydraulic fracture model for well spacing analysis and treatment design sensitivities. Results of the initial study indicated that stages in the new, higher interval had higher breakdown pressures than the lower interval. Additionally, the child well drilled in the lower interval had normal breakdown pressures in line with the parent well treatments. This suggests that treatment differences in the wells were ultimately due to depletion of the offset parent well. Based on the modeling efforts, optimal infill well spacing was determined based on the on-production time of the parent wells. The optimal treatment designs were also determined under the same conditions to minimize offset frac hits and unnecessary completion costs. This case study presents the use of a multi-disciplinary approach for well spacing and treatment optimization. The integration of a novel method of estimating pore pressure and depletion modeling workflows were used in an inventive way to understand depletion effects on future development.
Abstract The purpose of this paper is to present a technique to estimate hydraulic fracture (HF) length, fracture conductivity, and fracture efficiency using simple and rapid but rigorous reservoir simulation matching of historical production, and where available, pressure. The methodology is particularly appropriate for analysis of horizontal wells with multiple fractures in tight unconventional or unconventional resource plays. In our discussion, we also analyze the differences between the results from decline curve analysis (DCA) approach and the Science Based Forecasting (SBF) results that this work proposes. When we characterize fracture properties with SBF, we can do a better job of forecasting than if we randomly combine fracture properties and reservoir permeability together in a decline-curve trend. The forecasts are significantly different with SBF, therefore fracture characterization plays an important role and SBF uses this characterization to produce different (and better) forecasts.
Abstract The analyses of parent-child well performance is a complex problem depending on the interplay between timing, completion design, formation properties, direct frac-hits and well spacing. Assessing the impact of well spacing on parent or child well performance is therefore challenging. A naïve approach that is purely observational does not control for completion design or formation properties and can compromise well spacing decisions and economics and perhaps, lead to non-intuitive results. By using concepts from causal inference in randomized clinical trials, we quantify the impact of well spacing decisions on parent and child well performance. The fundamental concept behind causal inference is that causality facilitates prediction; but being able to predict does not imply causality because of association between the variables. In this study, we work with a large dataset of over 3000 wells in a large oil-bearing province in Texas. The dataset includes several covariates such as completion design (proppant/fluid volumes, frac-stages, lateral length, cluster spacing, clusters/stage and others) and formation properties (mechanical and petrophysical properties) as well as downhole location. We evaluate the impact of well spacing on 6-month and 1-year cumulative oil in four groups associated with different ranges of parent-child spacing. By assessing the statistical balance between the covariates for both parent and child well groups (controlling for completion and formation properties), we estimate the causal impact of well spacing on parent and child well performance. We compare our analyses with the routine naïve approach that gives non-intuitive results. In each of the four groups associated with different ranges of parent-child well spacing, the causal workflow quantifies the production loss associated with the parent and child well. This degradation in performance is seen to decrease with increasing well spacing and we provide an optimal well spacing value for this specific multi-bench unconventional play that has been validated in the field. The naïve analyses based on simply assessing association or correlation, on the contrary, shows increasing child well degradation for increasing well spacing, which is simply not supported by the data. The routinely applied correlative analyses between the outcome (cumulative oil) and predictors (well spacing) fails simply because it does not control for variations in completion design over the years, nor does it account for variations in the formation properties. To our knowledge, there is no other paper in petroleum engineering literature that speaks of causal inference. This is a fundamental precept in medicine to assess drug efficacy by controlling for age, sex, habits and other covariates. The same workflow can easily be generalized to assess well spacing decisions and parent-child well performance across multi-generational completion designs and spatially variant formation properties.
The advent of digital oil fields, data analytics, and artificial intelligence has led to an increase in the number of instruments installed at wellheads as well as an increase in the reliance on these instruments and the data they provide for the operation of the field. The critical nature of this equipment and their roles in the operation of the oil field also has led to the need for a system of remote monitoring of these wellheads to enable the detection of third-party intrusion at the wellhead area with the provision of video feedback on demand. The most popular security scheme currently deployed at these wellheads is the use of metal cages of different sizes, but the location of these wellheads provides vandals with ample time to cut through the metal cages because no means exists to detect their presence. The system presented in this paper uses a fiber-optic cable and cameras to provide intruder detection and identification. The fiber-optic cable is buried around the wellhead, and the flowlines from the wellhead and a wireless transmitter are coupled to the fiber-optic cable.
Abstract A comprehensive workflow was developed to support short and long-term unconventional Midland and Delaware Basin development strategy. The workflow is applied to every new pad to ensure child wells are targeting more of the virgin rock. The developed workflow considers pressure and stress changes around parent wells, landing strategy, completion optimization, frac order design, etc. A 3-D reservoir model was developed to estimate the depletion and the induced stress changes around the parent wells. Hydraulic fracture modeling is coupled with the flow simulation model to assess child wells fracture propagation under different scenarios. Different landing strategies were investigated to reduce depletion effects on Child wells. Child wells fracture and proppant fluid intensity was optimized to provide the optimum fracture interference. Certain technologies were successfully utilized to change the pressure and stress around the existing wells to properly alter child well fracture propagation towards virgin rock. Frac order was adjusted accordingly to benefit from the induced changes in reservoir pressure and stress around parent wells. The workflow was applied to areas in the Wolfcamp formation within the Midland and Delaware Basins. Results show the effectiveness of the developed workflow to maintain Basin development performance.
Abstract Determination of Iron Content in Triethylene glycol (TEG) samples is a very important indicator in measuring the system corrosion rate in oil and gas facilities. This study employed the application of an alternative/easy and reliable test method, which involved the use of a spectrophotometer for quantification of Iron concentration in tri ethylene glycol samples, that are used in sour gas dehydration units, rather than the sophisticated technique of Inductively Coupled Plasma Optical Emission Spectroscopy, ICP-OES. The main challenge was how to eliminate/minimize the significant interference from the carryover condensate hydrocarbons, BTEX, H2S and amine additives, which cause either precipitation with spectrophotometer reagents or turbid samples. The sample pretreatment process included: 1 - Sample digestion with dilution to eliminate the dissolved acid gases and the dissolved BTEX from the sample in acidic medium; 2 - pH adjustment from 9 – 10.5 to eliminate the amine additives interference with spectrophotometer reagents and 3 – Application of standard addition technique with certified reference material for iron with dilution, to reach the spectrophotometer detection limit and give intense color with more UV absorbance. The method was validated against ICP-OES and the results variance were within 10% acceptance criteria.
Tossapol, Tongkum (Mubadala Petroleum Thailand Ltd.) | Siritheerasas, Khamawat (Mubadala Petroleum Thailand Ltd.) | Abu Jafar, Feras (Mubadala Petroleum Thailand Ltd.) | Phu, Trinh Dinh (Schlumberger) | Hieu, Pham Nam (Schlumberger)
Abstract The Well X in Nong Yao field, is an infill-well designed for the Gulf of Thailand which presented several interesting challenges due to its complexity, tortuosity, and potential collision risks with other wells. This paper demonstrates the application of a Real-time Advanced Survey Correction (RASC) with Multi Station Analysis (MSA) to correct the Measurement While Drilling (MWD)'s azimuth. The Well X is a 3D Complex design with a high drilling difficulty index (DDI) at 6.9, high tortuosity of 316 degree, and which has an aggressive build on inclination and azimuthal U-turning well path. The well also creates difficult doglegs severity (DLS) up to 5.5deg/100ft, which is near the limit of the flexibility required to achieve the horizontal landing point. The conventional MWD survey, with proximity scanning with the nearby Well A, demonstrates high risk with a calculated Oriented Separation Factor (OSF) of 1.01. The RASC-MSA method is applied with a clearly defined workflow during execution in real-time and provide significant improvement in calculated OSF. RASC-MSA is applied for every 1,000 ft interval drilling below the 9.625in casing shoe. The workflow ensures that the directional driller follows the corrected survey along the well path and especially in the last 300 ft before reaching the electrical submersible pump (ESP) tangent section. The result from RASC-MSA, indicated a 29 ft lateral shift on the left side of the MWD standard surveys. Without this technique, Well X has a high potential to collide with Well A and Well B (Figure 1) as the actual OSF may less than 1 while drilling. The final 3D Least Distance proximity scanning with Well A shows a minimum OSF = 1.35, which is a 30% improvement compared to the conventional MWD survey. Another nearby well, Well B, indicates a minimum OSF=1.66 and passed the anti-collision OSF rule. In consideration of the drilling efficiency, availability, cost effectiveness and time saving, the RASC-MSA analysis to correct the MWD's azimuth are applied and the separation factor can be improved by 30%. In conclusion, the collision risk management technique applied successfully met the complex challenges of Well X, which was successfully drilled and safely delivered. Figure 1: 3D visualization to exhibit the collision issue between Well X and nearby existing Wells A and Well B.
The following are some of the most common sources of error in directional drilling. The survey instrument's performance depends on the package design elements, calibration performance, and quality control during operation. System performance will functionally depend on the borehole inclination, azimuth, geomagnetic-field vector, and geographical position. Because of the dependency on sensing Earth's spin rate, the performance of gyro compassing tools is inversely proportional to the cosine of the latitude of wellbore location. For magnetic tools, high latitudes result in weaker horizontal components of Earth's field.