Joint Pressure and Production Analysis to Understand Inter- and Intra-Zone Well Interference: A Midland Basin Case Study

2021 ◽  
Author(s):  
Qin Ji ◽  
Geoff Vernon ◽  
Juan Mata ◽  
Shannon Klier ◽  
Matthew Perry ◽  
...  
Keyword(s):  
Surface Pressure ◽  
Production Data ◽  
Well Performance ◽  
Pressure Data ◽  
Midland Basin ◽  
Well Production ◽  
Interference Test ◽  
The Impact ◽  
Fracture Growth ◽  
Pressure Analysis

Abstract This paper demonstrates how to use pressure data from offset wells to assess fracture growth and evolution through each stage by quantifying the impacts of nearby parent well depletion, completion design, and formation. Production data is analyzed to understand the correlation between fracture geometries, well interactions, and well performance. The dataset in this project includes three child wells and one parent well, landed within two targets of the Wolfcamp B reservoir in the Midland Basin. The following workflow helped the operator understand the completion design effectiveness and its impact to production:Parent well pressure analysis during completionIsolated stage offset pressure analysis during completionOne-month initial production analysis followed by one month shut-inPressure interference test: sequentially bringing wells back onlineProduction data comparison before and after shut-in period An integrated analysis of surface pressure data acquired from parent and offset child wells during completions provides an understanding of how hydraulic dimensions of each fracture stage are affected by fluid volume, proppant amount, frac stage order of operations, and nearby parent well depletion. Production data from all wells was analyzed to determine the impact of depletion on child well performance and to investigate the effects of varying completion designs. A pressure interference test based on Chow Pressure Group was also performed to further examine the connectivity between wells, both inter- and intra-zone. Surface pressure data recorded from isolated stages in the offset child wells during completions was used to resolve geometries and growth rates of the stimulated fractures. Asymmetric fracture growth, which preferentially propagates toward the depleted rock volume around the parent well, was identified at the heel of the child well closest to the parent. Fracture geometries of various child well stage groups were analyzed to determine the effectiveness of different completion designs and the impact of in situ formation properties. Analysis of parent well surface pressure data indicates that changing the completion design effectively reduced the magnitude of Fracture Driven Interactions (FDIs) between child and parent wells. Child well production was negatively impacted in the wells where the fracture boundary overlapped with the parent well depleted volume in the same formation zone. This study combines pressure and production analyses to better understand inter- and intra-zone interference between wells. The demonstrated workflow offers a very cost-effective approach to studying well interference. Observing and understanding the factors that drive fracture growth behavior enables better decision-making during completion design planning, mitigation of parent-child communication, and enhancement of offset well production.

Track Fractured Well Inflow Performance Using Historic Production Logging and Surface Well Performance Data in Sultanate of Oman

2022 ◽  
Author(s):  
Cornelis Adrianus Veeken ◽  
Yousuf Busaidi ◽  
Amira Hajri ◽  
Ahmed Mohammed Hegazy ◽  
Hamyar Riyami ◽  
...  
Keyword(s):  
Production Data ◽  
Hydraulic Fractures ◽  
Reservoir Pressure ◽  
Sultanate Of Oman ◽  
Well Performance ◽  
Pressure Depletion ◽  
Stress Dependent ◽  
Inflow Performance ◽  
The Impact ◽  
Surface Production

Abstract PDO operates about 200 deep gas wells in the X field in the Sultanate of Oman, producing commingled from the Barik gas-condensate and Miqrat lean gas reservoir completed by multiple hydraulic fracturing. Their inflow performance relation (IPR) is tracked to diagnose condensate damage, hydraulic fracture cleanup and differential reservoir pressure depletion. The best IPR data is collected through multi-rate production logging but surface production data serves as an alternative. This paper describes the process of deriving IPR's from production logging and surface production data, and then evaluates 20 years of historic IPR data to quantify the impact of condensate damage and condensate cleanup with progressive reservoir pressure depletion, to demonstrate the massive damage and slow cleanup of hydraulic fractures placed in depleted reservoirs, to show how hydraulic fractures facilitate the vertical cross-flow between isolated reservoir intervals, and to highlight that stress-dependent permeability does not play a major role in this field.

Key Factors in Shale Gas Modeling and Simulation

2014 ◽  
Vol 59 (4) ◽  
pp. 987-1004 ◽  
Author(s):  
Łukasz Klimkowski ◽  
Stanisław Nagy
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Production Performance ◽  
Hydraulic Fractures ◽  
Well Performance ◽  
Key Factors ◽  
Gas Well ◽  
Well Production ◽  
Multi Stage ◽  
The Impact

Abstract Multi-stage hydraulic fracturing is the method for unlocking shale gas resources and maximizing horizontal well performance. Modeling the effects of stimulation and fluid flow in a medium with extremely low permeability is significantly different from modeling conventional deposits. Due to the complexity of the subject, a significant number of parameters can affect the production performance. For a better understanding of the specifics of unconventional resources it is necessary to determine the effect of various parameters on the gas production process and identification of parameters of major importance. As a result, it may help in designing more effective way to provide gas resources from shale rocks. Within the framework of this study a sensitivity analysis of the numerical model of shale gas reservoir, built based on the latest solutions used in industrial reservoir simulators, was performed. The impact of different reservoir and hydraulic fractures parameters on a horizontal shale gas well production performance was assessed and key factors were determined.

scholarly journals Impact of scale, nuclear PDF and temperature variations on the interpretation of medium-modified jet production data from the LHC

2021 ◽  
Vol 2021 (4) ◽  
Author(s):  
A. Andronic ◽  
J. Honermann ◽  
M. Klasen ◽  
C. Klein-Bösing ◽  
J. Salomon
Keyword(s):  
Distribution Functions ◽  
Production Data ◽  
Crossover Temperature ◽  
Parton Distribution Functions ◽  
Temperature Variations ◽  
Nuclear Modification Factor ◽  
Nuclear Modification ◽  
Modification Factor ◽  
The Impact ◽  
Jet Structure

Abstract In this paper we present a study of in-medium jet modifications performed with JEWEL and PYTHIA 6.4, focusing on the uncertainties related to variations of the perturbative scales and nuclear parton distribution functions (PDFs) and on the impact of the initial and crossover temperature variations of the medium. The simulations are compared to LHC data for the jet spectrum and the nuclear modification factor. We assess the interplay between the choice of nuclear PDFs and different medium parameters and study the impact of nuclear PDFs and the medium on the jet structure via the Lund plane.

scholarly journals Defining and Quantifying Intermittency in the Power Sector

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3366
Author(s):  
Daniel Suchet ◽  
Adrien Jeantet ◽  
Thomas Elghozi ◽  
Zacharie Jehl
Keyword(s):  
Power Source ◽  
Production Data ◽  
Power Sector ◽  
Predictive Capacity ◽  
The Public ◽  
Current State ◽  
Definition Of ◽  
Quantitative Definition ◽  
The Impact

The lack of a systematic definition of intermittency in the power sector blurs the use of this term in the public debate: the same power source can be described as stable or intermittent, depending on the standpoint of the authors. This work tackles a quantitative definition of intermittency adapted to the power sector, linked to the nature of the source, and not to the current state of the energy mix or the production predictive capacity. A quantitative indicator is devised, discussed and graphically depicted. A case study is illustrated by the analysis of the 2018 production data in France and then developed further to evaluate the impact of two methods often considered to reduce intermittency: aggregation and complementarity between wind and solar productions.

Data-Driven Causal Analyses of Parent-Child Well Interactions for Well Spacing Decisions

2021 ◽  
Author(s):  
Rohan Sakhardande ◽  
Deepak Devegowda
Keyword(s):  
Causal Inference ◽  
Randomized Clinical Trials ◽  
Drug Efficacy ◽  
Complex Problem ◽  
Petroleum Engineering ◽  
Well Performance ◽  
Well Spacing ◽  
The Impact ◽  
Naive Approach ◽  
Parent Child

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.

Diagnostic Plots for Production Decline During the Transition of Oil Field Development From Depletion to Water Injection

2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov
Keyword(s):  
Water Injection ◽  
Simulation Models ◽  
Oil Field ◽  
Production Data ◽  
Oil Reservoir ◽  
Field Development ◽  
Well Production ◽  
Diagnostic Plots ◽  
Oil Field Development ◽  
Analytical Approaches

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.

Multidisciplinary Approach in The Permian Basin - A Geological, Statistical and Engineering Case Study to Production Results on the Wichita-Albany Formation

2015 ◽  
Author(s):  
Fabián Vera ◽  
Casee Lemons ◽  
Ming Zhong ◽  
William D. Holcomb ◽  
Randy F. LaFollette
Keyword(s):  
Design Patterns ◽  
Point Of View ◽  
Production Optimization ◽  
Multivariate Statistical ◽  
Data Set ◽  
Modern Approach ◽  
Well Production ◽  
Fracture Fluid ◽  
Major Factors ◽  
The Impact

Abstract This study compares reservoir characteristics, completion methods and production for 431 wells in 6 counties producing from the Wichita-Albany reservoir to assess major factors in production optimization and derive ultimate recovery estimates. The purpose of the study is to analyze completion design patterns across the study area by combining public and proprietary data for mining. Integrating several analyses of different nature and their respective methods like statistics, geology and engineering create a modern approach as well as a more holistic point of view when certain measurements are missing from the data set. Furthermore, multivariate statistical analysis allows modeling the impact of particular completion and stimulation parameters on the production outcome by averaging out the impact of all other variables in the system. In addition to completion type, more than 18 predictor variables were examined, including treatment parameters such as fracture fluid volume, year of completion, cumulative perforated length, proppant type, proppant amount, and county location, among others. In this sense, this contribution seems unique in unifying statistical, engineering, and geological perspectives into a singular point of view. This work also provides complementary views for well production consideration.

Machine Learning and Artificial Intelligence Provides Wolfcamp Completion Design Insight

2021 ◽  
Author(s):  
Robert Shelley ◽  
Oladapo Oduba ◽  
Howard Melcher
Keyword(s):  
Machine Learning ◽  
Water Saturation ◽  
Saturation Pressure ◽  
Ann Model ◽  
Permian Basin ◽  
Treatment Rate ◽  
Feed Forward Neural Network ◽  
Well Production ◽  
Reservoir Type ◽  
The Impact

Abstract The subject of this paper is the application of a unique machine learning approach to the evaluation of Wolfcamp B completions. A database consisting of Reservoir, Completion, Frac and Production information from 301 Multi-Fractured Horizontal Wolfcamp B Completions was assembled. These completions were from a 10-County area located in the Texas portion of the Permian Basin. Within this database there is a wide variation in completion design from many operators; lateral lengths ranging from a low of about 4,000 ft to a high of almost 15,000 ft, proppant intensities from 500 to 4,000 lb/ft and frac stage spacing from 59 to 769 ft. Two independent self-organizing data mappings (SOM) were performed; the first on completion and frac stage parameters, the second on reservoir and geology. Characteristics for wells assigned to each SOM bin were determined. These two mappings were then combined into a reservoir type vs completion type matrix. This type of approach is intended to remove systemactic errors in measuement, bias and inconsistencies in the database so that more realistic assessments about well performance can be made. Production for completion and reservoir type combinations were determined. As a final step, a feed forward neural network (ANN) model was developed from the mapped data. This model was used to estimate Wolfcamp B production and economics for completion and frac designs. In the performance of this project, it became apparent that the incorporation of reservoir data was essential to understanding the impact of completion and frac design on multi-fractured horizontal Wolfcamp B well production and economic performance. As we would expect, wells with the most permeability, higher pore pressure, effective porosity and lower water saturation have the greatest potential for hydrocarbon production. The most effective completion types have an optimum combination of proppant intensity, fluid intensity, treatment rate, frac stage spacing and perforation clustering. This paper will be of interest to anyone optimizing hydraulically fractured Wolfcamp B completion design or evaluating Permian Basin prospects. Also, of interest is the impact of reservoir and completion characteristics such as permeability, porosity, water saturation, pressure, offset well production, proppant intensity, fluid intensity, frac stage spacing and lateral length on well production and economics. The methodology used to evaluate the impact of reservoir and completion parameters for this Wolfcamp project is unique and novel. In addition, compared to other methodologies, it is low cost and fast. And though the focus of this paper is on the Wolfcamp B Formation in the Midland Basin, this approach and workflow can be applied to any formation in any Basin, provided sufficient data is available.

Surface Pressure Distribution on a Blade of a 10 m Diameter HAWT (Field Measurements versus Wind Tunnel Measurements)

2005 ◽  
Vol 127 (2) ◽  
pp. 185-191 ◽  
Author(s):  
T. Maeda ◽  
E. Ismaili ◽  
H. Kawabuchi ◽  
Y. Kamada
Keyword(s):  
Wind Tunnel ◽  
Surface Pressure ◽  
Field Measurements ◽  
Reynolds Numbers ◽  
Blade Surface ◽  
Pressure Data ◽  
Surface Pressure Distribution ◽  
Pressure Distributions ◽  
Wind Tunnel Data ◽  
Local Angle

This paper exploits blade surface pressure data acquired by testing a three-bladed upwind turbine operating in the field. Data were collected for a rotor blade at spanwise 0.7R with the rotor disc at zero yaw. Then, for the same blade, surface pressure data were acquired by testing in a wind tunnel. Analyses compared aerodynamic forces and surface pressure distributions under field conditions against analogous baseline data acquired from the wind tunnel data. The results show that aerodynamic performance of the section 70%, for local angle of attack below static stall, is similar for free stream and wind tunnel conditions and resemblances those commonly observed on two-dimensional aerofoils near stall. For post-stall flow, it is presumed that the exhibited differences are attributes of the differences on the Reynolds numbers at which the experiments were conducted.

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