scholarly journals A NEW APPROACH TO CALCULATE MUD INVASION IN RESERVOIRS USING WELL LOGS

2014 ◽  
Vol 32 (2) ◽  
pp. 215 ◽  
Author(s):  
Mariléa Ribeiro ◽  
Abel Carrasquilla
Keyword(s):  
Well Logs ◽  
Formation Damage ◽  
Drilling Mud ◽  
New Approach ◽  
Well Completion ◽  
Porosity And Permeability ◽  
Geophysical Logs ◽  
Mathematical Equations ◽  
Para Determinar ◽  
Geological Formations

ABSTRACT. Muds of different compositions are used in the drilling well process, to support the wall of the borehole along with maintenance of pressure, and toremove rock cuttings generated from the geological formations encountered by the drill bit. The drilling mud invades the formations and modifies the zones surroundingthe borehole, mainly, in terms of the physical properties of the rocks, such as porosity and permeability. The identification of this formation damage is important forreservoir characterization, and the subsequent well completion, as well as for the analysis of economic viability. Many years ago, Schlumberger developed a methodfor determining mud invasion diameter using the Tornado Chart. Today, practitioners in the oil industry use the Tornado Chart to present geophysical logs. Improvingupon Schlumberger’s methodology, Crain used mathematical equations to calculate the mud invasion diameter. In this study, we propose a polynomial mathematicalmethod to determine mud invasion diameter. Our method utilizes the same resistivity well logs, namely dual induction log and dual laterology, though different from thatof Schlumberger or Crain methods. The approach developed in this study considers the characteristics of the invasion process while quickly and accurately showingresults in the form of a log that can be visualized adjacent to other logs measured in the borehole.Keywords: formation damage, drilling mud invasion, resistivity well logs. RESUMO. No processo de perfuração de poços são utilizadas diferentes composições de lama com o propósito de suportar a parede do poço, manter a pressão e, ainda, remover os fragmentos de rocha originados pela broca ao atravessar as formações geológicas. A lama de perfuração invade as formações e modifica as zonas circundantes ao poço, sobretudo, em termos das propriedades físicas das rochas, tais como a porosidade e permeabilidade. A identificação deste tipo de dano à formação é importante, principalmente para a caracterização do reservatório, bem como nas atividades posteriores de conclusão do poço e, ainda, na análise deviabilidade econômica. Neste sentido, há muitos anos, a Schlumberger desenvolveu uma maneira de determinar o diâmetro de invasão da lama usando o GráficoTornado, que é utilizado até hoje na indústria do petróleo, essencialmente usando perfis geofísicos. Mais tarde, com o objetivo de melhorar a determinação do diâmetro de invasão, Crain usou equações matemáticas para calcular esse valor, fazendo correções na metodologia da Schlumberger. Neste trabalho, por outro lado, propõe-se um método matemático polinomial para determinar o diâmetro de invasão, que é diferente das metodologias desenvolvidas pela Schlumberger e por Crain, mas também utilizando os mesmos perfis resistivos de poços, ou seja, os perfis de indução (DIL) e laterolog (DLL) duplos. Desta forma, o procedimento desenvolvido no presentetrabalho mostrou-se rápido e preciso, pois considera melhor as características do processo de invasão, mostrando ainda os resultados sob a forma de um perfil ao lado de outros perfis medidos no poço, resultando, assim, numa visualização mais eficiente.Palavras-chave: dano à formação, invasão da lama de perfuração, perfis resistivos de poços.

Machine Learning for Multiple Petrophysical Properties Regression Based on Core Images and Well Logs in a Heterogenous Reservoir

2021 ◽  
Author(s):  
Tao Lin ◽  
Mokhles Mezghani ◽  
Chicheng Xu ◽  
Weichang Li
Keyword(s):  
Machine Learning ◽  
Model Building ◽  
Image Features ◽  
Well Logs ◽  
Model Complexity ◽  
Rock Properties ◽  
Core Analysis ◽  
Petrophysical Properties ◽  
Blind Test ◽  
Porosity And Permeability

Abstract Reservoir characterization requires accurate prediction of multiple petrophysical properties such as bulk density (or acoustic impedance), porosity, and permeability. However, it remains a big challenge in heterogeneous reservoirs due to significant diagenetic impacts including dissolution, dolomitization, cementation, and fracturing. Most well logs lack the resolution to obtain rock properties in detail in a heterogenous formation. Therefore, it is pertinent to integrate core images into the prediction workflow. This study presents a new approach to solve the problem of obtaining the high-resolution multiple petrophysical properties, by combining machine learning (ML) algorithms and computer vision (CV) techniques. The methodology can be used to automate the process of core data analysis with a minimum number of plugs, thus reducing human effort and cost and improving accuracy. The workflow consists of conditioning and extracting features from core images, correlating well logs and core analysis with those features to build ML models, and applying the models on new cores for petrophysical properties predictions. The core images are preprocessed and analyzed using color models and texture recognition, to extract image characteristics and core textures. The image features are then aggregated into a profile in depth, resampled and aligned with well logs and core analysis. The ML regression models, including classification and regression trees (CART) and deep neural network (DNN), are trained and validated from the filtered training samples of relevant features and target petrophysical properties. The models are then tested on a blind test dataset to evaluate the prediction performance, to predict target petrophysical properties of grain density, porosity and permeability. The profile of histograms of each target property are computed to analyze the data distribution. The feature vectors are extracted from CV analysis of core images and gamma ray logs. The importance of each feature is generated by CART model to individual target, which may be used to reduce model complexity of future model building. The model performances are evaluated and compared on each target. We achieved reasonably good correlation and accuracy on the models, for example, porosity R2=49.7% and RMSE=2.4 p.u., and logarithmic permeability R2=57.8% and RMSE=0.53. The field case demonstrates that inclusion of core image attributes can improve petrophysical regression in heterogenous reservoirs. It can be extended to a multi-well setting to generate vertical distribution of petrophysical properties which can be integrated into reservoir modeling and characterization. Machine leaning algorithms can help automate the workflow and be flexible to be adjusted to take various inputs for prediction.

scholarly journals Estimating reservoir permeability with borehole radar

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. H51-H60
Author(s):  
Feng Zhou ◽  
Iraklis Giannakis ◽  
Antonios Giannopoulos ◽  
Klaus Holliger ◽  
Evert Slob
Keyword(s):  
Water Saturation ◽  
Time Lapse ◽  
Drilling Mud ◽  
Invasion Depth ◽  
Initial Water ◽  
Oil Drilling ◽  
Reservoir Evaluation ◽  
Reservoir Permeability ◽  
Borehole Radar ◽  
Porosity And Permeability

In oil drilling, mud filtrate penetrates into porous formations and alters the compositions and properties of the pore fluids. This disturbs the logging signals and brings errors to reservoir evaluation. Drilling and logging engineers therefore deem mud invasion as undesired and attempt to eliminate its adverse effects. However, the mud-contaminated formation carries valuable information, notably with regard to its hydraulic properties. Typically, the invasion depth critically depends on the formation porosity and permeability. Therefore, if adequately characterized, mud invasion effects could be used for reservoir evaluation. To pursue this objective, we have applied borehole radar to measure mud invasion depth considering its high radial spatial resolution compared with conventional logging tools, which then allows us to estimate the reservoir permeability based on the acquired invasion depth. We investigate the feasibility of this strategy numerically through coupled electromagnetic and fluid modeling in an oil-bearing layer drilled using freshwater-based mud. Time-lapse logging is simulated to extract the signals reflected from the invasion front, and a dual-offset downhole antenna mode enables time-to-depth conversion to determine the invasion depth. Based on drilling, coring, and logging data, a quantitative interpretation chart is established, mapping the porosity, permeability, and initial water saturation into the invasion depth. The estimated permeability is in a good agreement with the actual formation permeability. Our results therefore suggest that borehole radar has significant potential to estimate permeability through mud invasion effects.

scholarly journals Prediction of Formation Damage, Fluid Loss and Rheological Properties of Water Based Mud with Corn Cob

2020 ◽  
Vol 5 (10) ◽  
pp. 1269-1273
Author(s):  
Godwin Chukwuma Jacob Nmegbu ◽  
Bright Bariakpoa Kinate ◽  
Bari-Agara Bekee
Keyword(s):  
Rheological Properties ◽  
High Pressures ◽  
Chemical Properties ◽  
Analytical Models ◽  
Formation Damage ◽  
Fluid Loss ◽  
Drilling Mud ◽  
Corn Cob ◽  
Core Samples ◽  
Water Based

The extent of damage to formation caused by water based drilling mud containing corn cob treated with sodium hydroxide to partially replace polyanionic cellulose (PAC) as a fluid loss control additive has been studied. Core samples were obtained from a well in Niger Delta for this study with a permeameter used to force the drilling mud into core samples at high pressures. Physio-chemical properties (moisture content, cellulose and lignin) of the samples were measured and the result after treatment showed reduction. The corn cob was combined with the PAC in the ratio of 25-75%, 50-50% and 75-25% in the mud. Analyzed drilling mud rheological properties such as plastic viscosity, apparent viscosity, yield point and gel strength all decreased as percentage of corn cob increased in the combination and steadily decreased as temperature increased to 200oF. Measured fluid loss and pH of the mud showed an increase in fluid loss and pH in mud sample with 100% corn cob. The extent of formation damage was determined by the differences in the initial and final permeability of the core samples. Experimental data were used to develop analytical models that can serve as effective tool to predict fluid loss, rheological properties of the drilling mud at temperature up to 200oF and percentage formation damage at 100 psi.

scholarly journals An Integrated Microfacies and Well Logs-Based Reservoir Characterization of Yamama Formation, Southern Iraq

2021 ◽  
pp. 3570-3586
Author(s):  
Mohanad M. Al-Ghuribawi ◽  
Rasha F. Faisal
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Effective Porosity ◽  
Well Logs ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Porosity And Permeability ◽  
South Of Iraq ◽  
Southern Iraq

     The Yamama Formation includes important carbonates reservoir that belongs to the Lower Cretaceous sequence in Southern Iraq. This study covers two oil fields (Sindbad and Siba) that are distributed Southeastern Basrah Governorate, South of Iraq. Yamama reservoir units were determined based on the study of cores, well logs, and petrographic examination of thin sections that required a detailed integration of geological data and petrophysical properties. These parameters were integrated in order to divide the Yamama Formation into six reservoir units (YA0, YA1, YA2, YB1, YB2 and YC), located between five cap rock units. The best facies association and petrophysical properties were found in the shoal environment, where the most common porosity types were the primary (interparticle) and secondary (moldic and vugs) . The main diagenetic process that occurred in YA0, YA2, and YB1 is cementation, which led to the filling of pore spaces by cement and subsequently decreased the reservoir quality (porosity and permeability). Based on the results of the final digital  computer interpretation and processing (CPI) performed by using the Techlog software, the units YA1 and YB2 have the best reservoir properties. The unit YB2 is characterized by a good effective porosity average, low water saturation, good permeability, and large thickness that distinguish it from other reservoir units.

scholarly journals Petrophysical Properties of Nahr Umar Formation in Nasiriya Oil Field

2020 ◽  
Vol 21 (3) ◽  
pp. 9-18
Author(s):  
Ahmed Abdulwahhab Suhail ◽  
Mohammed H. Hafiz ◽  
Fadhil S. Kadhim
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Oil Field ◽  
Well Logs ◽  
High Porosity ◽  
Reservoir Properties ◽  
Petrophysical Parameters ◽  
Resistivity Logs ◽  
Lithology Prediction ◽  
Porosity And Permeability

   Petrophysical characterization is the most important stage in reservoir management. The main purpose of this study is to evaluate reservoir properties and lithological identification of Nahr Umar Formation in Nasiriya oil field. The available well logs are (sonic, density, neutron, gamma-ray, SP, and resistivity logs). The petrophysical parameters such as the volume of clay, porosity, permeability, water saturation, were computed and interpreted using IP4.4 software. The lithology prediction of Nahr Umar formation was carried out by sonic -density cross plot technique. Nahr Umar Formation was divided into five units based on well logs interpretation and petrophysical Analysis: Nu-1 to Nu-5. The formation lithology is mainly composed of sandstone interlaminated with shale according to the interpretation of density, sonic, and gamma-ray logs. Interpretation of formation lithology and petrophysical parameters shows that Nu-1 is characterized by low shale content with high porosity and low water saturation whereas Nu-2 and Nu-4 consist mainly of high laminated shale with low porosity and permeability. Nu-3 is high porosity and water saturation and Nu-5 consists mainly of limestone layer that represents the water zone.

Case Study of Identifying and Minimizing Formation Damage in Tight Reservoirs Caused by Drilling Fluids in Abu Dhabi Onshore Operation Using Compatibility Coreflood Studies

2021 ◽  
Author(s):  
Raymond Saragi ◽  
Mohammad Husien ◽  
Dalia Salim Abdullah ◽  
Ryan McLaughlin ◽  
Ian Patey ◽  
...  
Keyword(s):  
Positive Impact ◽  
Abu Dhabi ◽  
Formation Damage ◽  
Drilling Fluids ◽  
Drilling Mud ◽  
Hydrocarbon Recovery ◽  
Tight Reservoirs ◽  
Filtrate Loss ◽  
Drilling Muds ◽  
Loss Control

Abstract A study was carried out to examine formation damage mechanisms caused by drilling fluids in tight reservoirs in several onshore oil fields in Abu Dhabi. Three phases of compatibility corefloods were carried out to identify potential to improve hydrocarbon recovery and examine reformulated/alternate drilling muds and treatment fluids. Interpretation was aided by novel Nano-CT quantifications and visualisations. The first phase examined the current drilling muds and showed inconsistent filtrate loss control alongside high levels of permeability alteration. These alterations were caused by retention of drilling mud constituents in the near-wellbore and incomplete clean-up of drilling mud-cakes. Based upon these results, reformulated and alternate drilling muds were examined in Phase 2, and there was a positive impact upon both filtrate loss and permeability, although the Nano-CT quantifications and visualisations showed that drilling mud constituents were still having an impact upon permeability. Candidate treatment fluids were examined in Phase 3, with all having a positive impact and the best performance coming from 15% HCl and an enzyme-based treatment. The interpretative tools showed that these treatments had removed drilling mud-cakes, created wormholes, and bypassed the areas where constituents were retained. The compatibility corefloods on tight reservoir core, alongside high-resolution quantifications and visualisations, therefore identified damaging mechanisms, helped identify potential to improve hydrocarbon recovery, and identify treatment fluid options which could be used in the fields.

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