Simultaneous Solution for Ultimate Recovery, Original Hydrocarbon in Place, and Permeability from Production Data Analysis with Application to the Eagle Ford Shale

2016 ◽  
Author(s):  
U l Naeem ◽  
Dahraj Hussain ◽  
Kareem Al Khamees ◽  
Jeffrey G. Callard ◽  
Deepak Devegowda
Keyword(s):  
Data Analysis ◽  
Production Data ◽  
Simultaneous Solution ◽  
Eagle Ford Shale ◽  
Eagle Ford

Production Data Analysis in Eagle Ford Shale Gas Reservoir

2012 ◽  
Author(s):  
Bingxiang Xu ◽  
Manouchehr Haghighi ◽  
Dennis A. Cooke ◽  
XiangFang Li
Keyword(s):  
Data Analysis ◽  
Shale Gas ◽  
Production Data ◽  
Eagle Ford Shale ◽  
Gas Reservoir ◽  
Eagle Ford ◽  
Shale Gas Reservoir

Production Forecast, Analysis and Simulation of Eagle Ford Shale Oil Wells

2015 ◽  
Author(s):  
Basel Alotaibi ◽  
David Schechter ◽  
Robert A. Wattenbarger
Keyword(s):  
Production Rate ◽  
Oil Production ◽  
Oil Wells ◽  
Unconventional Reservoirs ◽  
Production Data ◽  
Eagle Ford Shale ◽  
Production Forecast ◽  
Eagle Ford ◽  
Type Curves ◽  
Single Well

Abstract In previous works and published literature, production forecast and production decline of unconventional reservoirs were done on a single-well basis. The main objective of previous works was to estimate the ultimate recovery of wells or to forecast the decline of wells in order to estimate how many years a well could produce and what the abandonment rate was. Other studies targeted production data analysis to evaluate the completion (hydraulic fracturing) of shale wells. The purpose of this work is to generate field-wide production forecast of the Eagle Ford Shale (EFS). In this paper, we considered oil production of the EFS only. More than 6 thousand oil wells were put online in the EFS basin between 2008 and December 2013. The method started by generating type curves of producing wells to understand their performance. Based on the type curves, a program was prepared to forecast the oil production of EFS based on different drilling schedules; moreover drilling requirements can be calculated based on the desired production rate. In addition, analysis of daily production data from the basin was performed. Moreover, single-well simulations were done to compare results with the analyzed data. Findings of this study depended on the proposed drilling and developing scenario of EFS. The field showed potential of producing high oil production rate for a long period of time. The presented forecasted case gave and indications of the expected field-wide rate that can be witnessed in the near future in EFS. The method generated by this study is useful for predicting the performance of various unconventional reservoirs for both oil and gas. It can be used as a quick-look tool that can help if numerical reservoir simulations of the whole basin are not yet prepared. In conclusion, this tool can be used to prepare an optimized drilling schedule to reach the required rate of the whole basin.

Bayesian Probabilistic Decline-Curve Analysis Reliably Quantifies Uncertainty in Shale-Well-Production Forecasts

SPE Journal ◽  
2014 ◽  
Vol 19 (06) ◽  
pp. 1047-1057 ◽  
Author(s):  
Xinglai Gong ◽  
Raul Gonzalez ◽  
Duane A. McVay ◽  
Jeffrey D. Hart
Keyword(s):  
Horizontal Well ◽  
Production Data ◽  
Eagle Ford Shale ◽  
Eagle Ford ◽  
Production Uncertainty ◽  
Bayesian Methodology ◽  
Decline Curve Analysis ◽  
Decline Curve ◽  
Decline Curves ◽  
Cumulative Production

Summary Several analytical decline-curve models have been developed recently for shale-gas wells (Ilk et al. 2008; Anderson et al. 2010; Valko and Lee 2010). However, these authors did not quantify the uncertainty in production forecasts and reserves estimates. This is important because most shale plays are in the early stages of production and virtually any method will have large uncertainty when there are limited production data available. Jochen and Spivey (1996) and Cheng et al. (2010) developed bootstrap methods that can generate probabilistic decline forecasts and quantify reserves uncertainty. Hindcasts with the modified bootstrap method (MBM) (Cheng et al. 2010) provide good coverage of the true cumulative production. However, the authors did not show they can quantify reserves uncertainty with limited production data in unconventional plays. In this paper, we introduce a Bayesian probabilistic methodology using Markov-chain Monte Carlo (MCMC) combined with Arps' decline-curve analysis. We tested this model on two data sets: Barnett shale horizontal-well gas production with more than 7 years of history and Eagle Ford shale horizontal-well oil production with more than 1 year of history. In both cases, P50 hindcasts were very close to true cumulative production and P90 and P10 hindcasts quantified the cumulative production uncertainty reliably with as little as 6 months of production available for matching. In this Bayesian methodology, the decline-curve parameters qi, Di, and b are assumed to be random variables instead of parameters to be modified to obtain a best fit. A Markov chain of the decline-curve parameters is constructed by use of MCMC with the Metropolis algorithm (random walk). We developed the model by performing hindcasts with the Barnett case study consisting of 197 horizontal gas wells with more than 7 years of production. The prior distribution, proposal distribution, and likelihood function were calibrated so the probabilistic decline curves quantified the cumulative-production uncertainty reliably with as little as 6 months of data. The same model was then tested with analysis of Eagle Ford shale oil production from 536 wells; the probabilistic decline curves quantified the cumulative-production uncertainty reasonably well by changing only the prior distribution. The proposed Bayesian methodology provides a means and a workflow to generate probabilistic decline-curve forecasts and quantify reserves uncertainty in shale plays quickly and reliably. This Bayesian methodology can also be applied with other analytical decline-curve models if desired.

Ultra-Fast, Pad-Scale Modeling of Hydraulic Fracturing and Depletion for Optimizing Development Plans in the Eagle Ford Play

2021 ◽  
Author(s):  
Egor Dontsov ◽  
Roberto Suarez-Rivera ◽  
Rohit Panse ◽  
Christopher Quinn ◽  
Heather LaReau ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Field Data ◽  
Production Data ◽  
Depletion Zone ◽  
Eagle Ford Shale ◽  
Large Reservoir ◽  
Eagle Ford ◽  
Well Spacing ◽  
Plausible Model ◽  
Field Production

AbstractAs the number of wells drilled in regions with existing producing wells increases, understanding the detrimental impact of these by the depleted zone around parent wells becomes more urgent and important. This understanding should include being able to predict the extent and heterogeneity of the depleted region near the pre-existing wells, the resulting altered stress field, and the effect of this on newly created fractures from adjacent child wells. In this paper we present a workflow that addresses the above concern in the Eagle Ford shale play, using numerical simulations of fracturing and reservoir flow, to define the effect of the depletion zone on child wells and match their field production data. We utilize an ultra-fast hydraulic fracture and depletion model to conduct several hundred numerical simulations, with varying values of permeability and surface area, seeking for cases that match the field production data. Multiple solutions exist that match the field data equally well, and we used additional field production data of parent-child well-interaction, to select the most plausible model. Results show that the depletion zone is strongly non-uniform and that large reservoir regions remain undepleted. We observe two important effects of the depleted zone on fractures from child wells drilled adjacent to the parents. Some fractures propagate towards low pressure zones and do not contribute to production. Others are repelled by the higher stress region that develops around the depletion zone, propagate into undepleted rock, and have production rates commensurate to that from other child wells drilled away from depleted region. The observations are validated by the field data. Results are being used to optimize well placement and well spacing for subsequent field operations, with the objective to increase the effectiveness of the child wells.

EXAMINING WATER AND PROPPANT DEMANDS ASSOCIATED WITH PETROLEUM PRODUCTION FROM THE EAGLE FORD SHALE, GULF COAST, TEXAS

2017 ◽  
Author(s):  
Nicholas J. Gianoutsos ◽  
◽  
Seth S. Haines ◽  
Brian Varela ◽  
Katherine Whidden
Keyword(s):  
Gulf Coast ◽  
Eagle Ford Shale ◽  
Eagle Ford ◽  
Petroleum Production
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