Development of New Sand Consolidation Fluid and Field Application in Shallow Gas Reservoirs

2011 ◽  
Author(s):  
Michael James Fuller ◽  
Ricardo Andres Gomez ◽  
Joel Gill ◽  
Cesar Roberto Guimaraes De Carvalho ◽  
Ardestya Ferta Abdurachman ◽  
...  
Keyword(s):  
Field Application ◽  
Gas Reservoirs ◽  
Shallow Gas

A Study of Downhole Drillable Pulsing Cementing Device with Low Frequency Self-Excited Hydraulic Oscillation and its Field Application

2012 ◽  
Vol 450-451 ◽  
pp. 1536-1539
Author(s):  
Cui Ping Nie ◽  
Deng Sheng Ye
Keyword(s):  
Setting Time ◽  
Low Frequency ◽  
Field Application ◽  
Displacement Efficiency ◽  
Cement Slurry ◽  
Gas Reservoirs ◽  
Gas Field ◽  
Gas Well ◽  
Hydraulic Oscillation ◽  
Injection Technology

Abstract: Usually we pay more attention on how to improve gas well cementing quality in engineering design and field operations, and there are so many studies on cement agents but few researches on cement slurry injection technology. The field practice proved that conventional cementing technology can not ensure the cementing quality especially in gas well and some abnormal pressure wells. Most of the study is concentrated on cement agents and some cementing aspects such as wellbore condition, casing centralization etc. All the factors analysis on cementing quality has pointed out that a combination of good agents and suitable measurements can improve cementing quality effectively. The essential factor in cementing is to enhance the displacement efficiency, but normal hole condition and casing centralization are the fundamental for cementing only. Pulsing cementing is the technology that it can improve the displacement efficiency especially in reservoir well interval, also it can shorten the period from initial to ultimate setting time for cement slurry or improve thickening characteristics, and then to inhibit the potential gas or water channeling. Based on systematically research, aiming at improving in 7″ liner cementing, where there are multi gas reservoirs in long interval in SiChuan special gas field, well was completed with upper 7″ liner and down lower 5″ liner, poor cementing bonding before this time. So we stressed on the study of a downhole low frequency self-excited hydraulic oscillation pulsing cementing drillable device and its application, its successful field utilization proved that it is an innovative tool, and it can improve cementing quality obviously.

Review of Case Histories of Two Shallow-Gas Reservoirs in China

2003 ◽  
Author(s):  
Ruyan Sheng ◽  
Zhenquan Li ◽  
Hua Liu ◽  
Xiyong Xiang
Keyword(s):  
Case Histories ◽  
Gas Reservoirs ◽  
Shallow Gas

Reserves Determination Using Type Curve Matching and Extended Material Balance Methods in the Medicine Hat Shallow Gas Field

1994 ◽  
Author(s):  
S. L. West ◽  
P. J. R. Cochrane
Keyword(s):  
Material Balance ◽  
Poor Quality ◽  
Curve Matching ◽  
Pressure Data ◽  
Gas Reservoirs ◽  
Shallow Gas ◽  
Gas Field ◽  
Type Curve ◽  
Balance Analysis ◽  
Diffusivity Equation

Tight shallow gas reservoirs in the Western Canada Basin present a number of unique challenges in accurately determining reserves. Traditional methods such as decline analysis and material balance are inaccurate due to the formations' low permeabilities and poor pressure data. The low permeabilities cause long transient periods not easily separable from production decline using conventional decline analysis. The result is lower confidence in selecting the appropriate decline characteristics (exponential or harmonic) which significantly impacts recovery factors and remaining reserves. Limited, poor quality pressure data and commingled production from the three producing zones results in non representative pressure data and hence inaccurate material balance analysis. This paper presents the merit of two new methods of reserve evaluation which address the problems described above for tight shallow gas in the Medicine Hat field. The first method applies type curve matching which combines the analytical pressure solutions of the diffusivity equation (transient) with the empirical decline equation. The second method is an extended material balance which incorporates the gas deliverability theory to allow the selection of appropriate p/z derivatives without relying on pressure data. Excellent results were obtained by applying these two methodologies to ten properties which gather gas from 2300 wells. The two independent techniques resulted in similar production forecasts and reserves, confirming their validity. They proved to be valuable, practical tools in overcoming the various challenges of tight shallow gas and in improving the accuracy in gas reserves determination in the Medicine Hat field.

Chalupki Debnianskie Field – Improving Drilling Success in Shallow Gas Reservoirs with VectorSeis®

2003 ◽  
Author(s):  
D.J. Tessman ◽  
E. Gruszczyk ◽  
Z. Trzesniowski ◽  
P. Misiaczek ◽  
P. Brettwood
Keyword(s):  
Gas Reservoirs ◽  
Shallow Gas

Multiscale Formation Damage Mechanisms and Control Technology for Deep Tight Clastic Gas Reservoirs

SPE Journal ◽  
2021 ◽  
pp. 1-16
Author(s):  
Yijun Wang ◽  
Yili Kang ◽  
Lijun You ◽  
Chengyuan Xu ◽  
Xiaopeng Yan ◽  
...  
Keyword(s):  
Drilling Fluid ◽  
Damage Control ◽  
Production Capacity ◽  
Damage Mechanism ◽  
Field Application ◽  
Formation Damage ◽  
Fluid Loss ◽  
Drilling Process ◽  
Gas Reservoirs ◽  
Filtration Loss

Summary Severe formation damage often occurs during the drilling process, which significantly impedes the timely discovery, accurate evaluation, and efficient development of deep tight clastic gas reservoirs. The addition of formation protection additives into drilling fluid after diagnosing the damage mechanism is the most popular technique for formation damage control (FDC). However, the implementation of traditional FDC measures does not consider the multiscale damage characteristics of the reservoir. The present study aims at filling this gap by providing a complete and systematic damage control methodology based on multiscale FDC theory. First, the characteristics of multiscale seepage channels were described through petrology, petrophysics, and well-history data. Subsequently, based on laboratory formation damage evaluation experiments, the formation damage mechanism of each seepage scale was determined. Finally, based on the multiscale formation damage mechanism, a systematic multiscale FDC technology was proposed. Through the use of optimized drilling fluid based on multiscale FDC theory, high-permeability recovery ratio (PRR), high-pressure bearing capacity of plugging zone, and low cumulative filtration loss were observed by laboratory validation experiments. Shorter drilling cycle, less drill-in-fluid loss, lower skin factor, and higher production rates were obtained by using the optimized FDC drilling fluid in field application. This multiscale FDC theory shows excellent results in minimizing formation damage, maintaining original production capacity, and effectively developing gas reservoirs with multiscale pore structure characteristics.

Machine Learning Technology to Improve Precision and Accelerate Screening Shallow Gas Potentials in Tunu Shallow Gas Zone, PT Pertamina Hulu Mahakam

2021 ◽  
Author(s):  
R. Herbet
Keyword(s):  
Machine Learning ◽  
Learning Technology ◽  
Gas Reservoirs ◽  
Shallow Gas ◽  
Gas Field ◽  
East Kalimantan ◽  
Main Challenge ◽  
Shallow Zone ◽  
Learning Probability ◽  
Mahakam Delta

Tunu is a giant gas field located in the present-day Mahakam Delta, East Kalimantan, Indonesia. Tunu gas produced from Tunu Main Zone (TMZ), between 2500-4500 m TVDSS and Tunu Shallow Zone (TSZ) located on depth 600 - 1500 m TVDSS. Gas reservoirs are scattered along the Tunu Field and corresponds with fluio-deltaic series. Main lithologies are shale, sand, and coal layers. Shallow gas trapping system is a combination of stratigraphic features, and geological structures. The TSZ development relies heavily on the use seismic to assess and identify gas sand reservoirs as drilling targets. The main challenge for conventional use of seismic is differentiating the gas sands from the coal layers. Gas sands are identified by an established seismic workflow that comprises of four different analysis on pre-stack and angle stacks, CDP gathers, amplitude versus angle(AVA), and inversion/litho-seismic cube. This workflow has a high success rate in identifying gas, but requires a lot of time to assess the prospect. The challenge is to assess more than 20,000 shallow objects in TSZ, it is important to have a faster and more efficient workflow to speed up the development phase. The aim of this study is to evaluate the robustness of machine learning to quantify seismic objects/geobodies to be gas reservoirs. We tested various machine learning methods to fit learn geological Tunu characteristic to the seismic data. The training result shows that a gas sand geobody can be predicted using combination of AVA gather, sub-stacks and seismic attributes with model precision of 80%. Two blind wells tests showed precision more than 95% while other final set tests are under evaluated. Detectability here is the ability of machine learning to predicted the actual gas reservoir as compared to the number of gas reservoirs found in that particular wells test. Outcome from this study is expected to accelerate gas assessment workflow in the near future using the machine learning probability cube, with more optimized and quantitative workflow by showing its predictive value in each anomaly.

Chałupki Dębniańskie Field: Improving drilling success in shallow gas reservoirs with VectorSeis

First Break ◽  
2003 ◽  
Vol 21 (2) ◽  
Author(s):  
E. Gruszczyk ◽  
Z. Tresnioswki ◽  
P. Misiaczek ◽  
P. Brettwood ◽  
J. Tessman
Keyword(s):  
Gas Reservoirs ◽  
Shallow Gas
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