Research on low productivity and logging evaluation of coalbed methane wells: a case study of the Baode block

In this work, we analyzed the causes of low productivity in coalbed methane (CBM) wells by considering the Baode block as a case study. In addition to investigating the reasons for low productivity in mature CBM wells, we developed logging interpretation methods to reassess and tap the remaining potential of such wells to revitalize existing resources. Given the development status of the Baode block, which is characterized by a high proportion of mature wells, rapidly declining production, and low wellhead pressure, we integrated logging, fracturing, well testing, production testing, and production dynamic data in this study to summarize the causes of low productivity. Furthermore, we established a well potential evaluation method for the mature wells in Baode block based on key indicators like the logging parameters, reservoir conditions, structural conditions, engineering conditions, and estimated gas production. The final outcomes of this work include identification of the potential well segments and their levels as well as stimulation plans for the identified wells. Application of the proposed method to the Baode block yielded significant results as follows: the average production increase in the stimulated potential wells exceeded 1,000 cubic meters per day, and the average single-well increase in the estimated ultimate recovery (EUR) exceeded 3 million cubic meters. Thus, the proposed approach provides valuable guidance for understanding the causes of low productivity in mature wells as well as enhancing their reserves and production.

1 Introduction

The Baode block is one of the most successfully developed and largest-scale medium-to-low-rank coalbed methane (CBM) fields in China (Xu et al., 2023). It belongs to the northern section of the Jinxi Fold Belt in terms of the structural location and has the overall shape of a large monocline structure with a gentle westward dip (Zhao et al., 2014). Several years of continuous development and production in the Baode block have resulted in increasingly prominent operational challenges, including a rising proportion of aging wells, accelerated decline in the production capacity, excess water production in the wellbores, and gradually decreasing wellhead pressure. Additionally, there is a significant discrepancy between the original geological understanding as well as reservoir evaluation and the actual production performance. In response to these issues, numerous scholars have conducted relevant research. For instance, Zhang et al. (2023), Wen et al. (2018), Zhao (2017), and Zhang et al. (2022) analyzed and studied the geological factors as well as production capacity influences of CBM. Zhang et al. (2021), Jiang (2020), Li et al. (2021), Dong et al. (2016), and Liu et al. (2013) analyzed the CBM production capacity through coal quality parameters and comprehensive logging evaluations. Studies suggest that the factors influencing CBM production capacity in the Baode block primarily stem from three aspects: geology, engineering, and production. The geological factors include coal seam structure, coal seam thickness, groundwater fluid potential, gas content, permeability, and ratio of critical desorption pressure to reservoir pressure; the engineering and technical factors include well spacing, total fracturing fluid volume, and sand volume; the production factors include rate of bottomhole pressure decline, rate of dynamic liquid level decline, production tubing, and wellbore flow regimes.

In this study, we combined the latest research achievements in detailed gas reservoir characterizations and analysis of the effects of implementing comprehensive adjustments over the years to assess the existing problems and challenges in the block. Currently, the main challenges include insufficiently thorough reservoir research, suboptimal results from conventional fracturing in some wells, rapid decline in production from older wells, a high proportion of low-yield and inefficient wells, complex wellbore conditions, and production fluctuations caused by surface system problems. The conditions for maintaining and increasing production in the block are severe, which make it imperative to analyze the causes of low production in the Baode block, conduct comprehensive logging reevaluations, and formulate suitable potential tapping strategies to facilitate efficient gas-field development. Based on comprehensive analyses of the logging, geological, engineering, and production data from the Baode block, we concluded that microstructural differences are the primary geological factor responsible for localized low production. Positive microstructural highs yield better gas production results compared to negative microstructural lows. Correspondingly, the main engineering factor is inadequate reservoir stimulation that limits the drainage and pressure reduction desorption range, resulting in lower permeability and reservoir utilization rates; the primary production factors are formation blockage and wellbore pump sticking caused by coal fines production, which restrict the productivity of the gas well.

2 Analysis of low production causes

2.1 Microstructural differences

Based on studies of the geological structural characteristics of the Baode block, a comparison of the geological and logging parameter features between the low-production and high-production wells in different regions of the block reveals that the key influencing factor is the microstructural amplitudes of the coal seams (Yan et al., 2020). Microstructures can be broadly categorized into four types as positive microstructures, gentle microstructures, negative microstructures, and steep structural zones (Yan et al., 2022). The block is further subdivided into nine secondary fold belts, including five positive and four negative microstructural belts.

A comparative analysis of the geological characteristics and production parameters between the wells in the positive and negative microstructural belts reveals the following. As desorbed CBM continuously migrates and accumulates in the structural highs to form new gas reservoirs in the positive microstructural zones, these areas exhibit relatively high overall production. In contrast, the negative microstructural zones that are characterized by dense structural lines and relatively high stress values pose greater challenges in terms of fracturing and stimulation, leading to lower overall productivity in these regions, as shown in Table 1.

Table 1

Table 1. Statistical table of gas production from typical wells with different structural characteristics in the Baode block.

Based on the production history and current production dynamics data of wells in different development units, we take the B2 well area as an example to show that the production is distinctly zoned along the narrow positive microstructural belt. Outside the belt, three wells have production ranges of 2,500–5,000 cubic meters per day, with an average production of 3,500 cubic meters per day; inside the belt, three wells have production ranges of 200–500 cubic meters per day, with an average production of 367 cubic meters per day.

2.2 Inadequate reservoir stimulation

Fracturing is the conventional and primary stimulation measure used for CBM extraction. Optimization of the fracturing operation parameters is a key issue for enhancing the productivity of CBM wells as well as achieving efficient development and utilization of CBM (Tian et al., 2014). Statistical analysis of the fracturing information from the Baode block based on data from 176 conventional fracturing operations shows that the average fracturing fluid volume ranges from 800 to 1,100 cubic meters and average sand volume ranges from 20 to 60 cubic meters, with the single-well daily gas production generally ranging between 300 and 1,500 cubic meters. In contrast, data from six large-scale fracturing operations in the Baode block indicate that the average fracturing fluid volume is 1,100–2,200 cubic meters and average sand volume is 160–530 cubic meters, with the single-well daily gas production reaching as high as 1,600–3,500 cubic meters. The average daily gas production from large-scale fracturing wells is 2–5 times that from conventional fracturing wells. Taking the B1-78 well pad as an example (as shown in Table 2), we see that the pad includes four wells with large-scale fracturing and two wells with conventional fracturing operations. A comparative analysis of these wells shows that large-scale fracturing results in 2.1-times higher average daily gas production than conventional fracturing, along with a 2.2-fold increase in the fracturing scale. Based on this analysis, we conclude that under full consideration of the geological influencing factors, significantly increasing the fluid and sand volumes as well as transitioning from matrix acid fracturing to volume fracturing can markedly enhance the single-well CBM production (Figure 1). In other words, increasing the fracturing scale can improve the reservoir permeability and desorption range more effectively, thereby unlocking the gas production potentials of individual wells.

Table 2

Table 2. Statistical table of gas production for different fracturing scales at the B1-78 well pad.

Figure 1

Figure 1. Crossplot showing total sand volumes in large-scale fracturing against stable daily gas production in the Baode block.

2.3 Formation blockage and coal fines pump sticking

During the drainage and production processes of CBM wells, changes in the reservoir stresses can easily cause fracturing of the coal matrix, leading to the generation of coal fines. This can cause gas locking in the formation, blockage of flow channels by the coal fines, and closure of ground stresses, all of which can reduce formation permeability and even cause pump sticking, thereby impacting development and production negatively (Meng et al., 2017). The generation of coal fines is significantly influenced by artificial stimulation or drainage and production systems. To effectively control the generation and discharge of coal fines from reservoirs, it is necessary to precisely organize and manage the drainage and production systems for CBM wells. In daily production, comprehensive analyses can be conducted through production curves, changes in the color of the produced water, dynamometer card detection, and pump inspection to identify the root causes and propose corresponding wellbore treatment measures.

In the Baode block, some low-productivity wells are affected by coal fines and scale blockage. During the later stages of production in drainage wells, there are notable declines in both gas and water production. By analyzing the color of the produced water, dynamometer cards, and pump inspection results, we determined that these wells experienced blockage of the flow channels or pump sticking due to coal fines.

3 Potential evaluation methods

By summarizing the causes of low production in old wells in the Baode block and based on coal core experimental data, we integrate logging, gas testing, and production data in this study to determine CBM logging interpretation methods. In the process, we also establish some key logging evaluation models and coal seam evaluation standards for the coal structure, gas content, and in situ stress to assess the resource potentials of old CBM wells comprehensively.

3.1 Establishing key logging evaluation models for coal seams

3.1.1 Coal structure

Based on the coal structure and logging curve characteristics of the Baode block, we established a logging identification chart and an interpretation model for the coal structure (Figures 2, 3). The distribution features of the chart indicate that more fragmented coal structures are more prone to borehole enlargement, larger borehole diameters, higher natural gamma rays, and lower resistivities.

Figure 2

Figure 2. Crossplot of borehole diameter (CAL) vs. natural gamma ray (GR) level.

Figure 3

Figure 3. Crossplot of borehole diameter (CAL) vs. resistivity (RD).

Based on the correlation between coal structure and logging interpretation parameters, a coal structure discrimination factor can be introduced as follows:

$\text{Coal\_}\text{Structure}=\mathrm{f}\left(\text{GR},\text{CAL},{\mathrm{R}}_{\mathrm{t}}\right).(1)$

In Equation 1, Coal_Structure is the coal structure discrimination factor (dimensionless), f is the discrimination relationship function (dimensionless), GR is the natural gamma ray level (in API units), CAL is the borehole diameter (in cm), and R_t is the deep resistivity (in Ω·m).

By establishing the coal structure discrimination factor, the intervals corresponding to different types of coal structures can be defined to enable their quantitative characterization through the logging interpretation parameters, as shown in Table 3.

Table 3

Table 3. Table of discrimination intervals for coal structures in the Baode block.

3.1.2 Coal seam gas content

In the study area, the gas content was interpreted using an adsorbed gas model. Based on the Langmuir equation and isothermal adsorption experimental data, the adsorption isotherms of the coal seams were fitted with the logging data to establish a separate interpretation model for the gas content of each coal seam.

In Figure 4, the horizontal axis represents the logging gamma ray (GR) level (in API units) and vertical axis represents the Langmuir volume (VL; in cm³/g). In Figure 5, the horizontal axis represents the logging ash content (Ad; in %) and vertical axis represents the Langmuir pressure (PL; in MPa). In Figure 6, the horizontal axis represents the logging vitrinite content (Vit; in %) and vertical axis represents the Langmuir pressure (in MPa).

$\mathrm{V}={\text{VL}}^{*}\mathrm{P}/\left(\text{PL}+\mathrm{P}\right).(2)$

Figure 4

Figure 4. Crossplot of logging gamma ray (GR) level vs. core Langmuir volume (VL).

Figure 5

Figure 5. Crossplot of logging ash content (Ad) vs. core Langmuir pressure (PL).

Figure 6

Figure 6. Crossplot of logging vitrinite content (Vit) vs. core Langmuir pressure (PL).

In Equation 2, V is the adsorbed gas content (in m³/t), VL is the Langmuir volume (in m³/t), PL is the Langmuir pressure (in MPa), and P is the formation pressure (in MPa).

3.1.3 In situ stress

The stress values at the coal seam roofs and floors play crucial roles in their sealing properties. The common in situ stress interpretation models include the composite spring empirical model, Huang’s empirical model, and triaxial stress model. Based on comparative analyses of the production practices in the Baode block, we found that the composite spring empirical model showed better adaptability for the region; therefore, we adopt the composite spring empirical model in this study.

${\mathrm{\sigma }}_{\mathrm{h}}=\frac{\mathrm{v}}{1-\mathrm{v}}\left({\mathrm{\sigma }}_{\mathrm{v}}-\mathrm{\alpha }{\mathrm{P}}_{\mathrm{p}}\right)+\frac{\mathrm{E}{\mathrm{\epsilon }}_{\mathrm{h}}}{1-{\mathrm{v}}^2}+\frac{\text{vE}{\mathrm{\epsilon }}_{\mathrm{H}}}{1-{\mathrm{v}}^2}+\mathrm{\alpha }{\mathrm{P}}_{\mathrm{p}},(3)$

${\mathrm{\sigma }}_{\mathrm{H}}=\frac{\mathrm{v}}{1-\mathrm{v}}\left({\mathrm{\sigma }}_{\mathrm{v}}-\mathrm{\alpha }{\mathrm{P}}_{\mathrm{p}}\right)+\frac{\mathrm{E}{\mathrm{\epsilon }}_{\mathrm{H}}}{1-{\mathrm{v}}^2}+\frac{\text{vE}{\mathrm{\epsilon }}_{\mathrm{h}}}{1-{\mathrm{v}}^2}+\mathrm{\alpha }{\mathrm{P}}_{\mathrm{p}}.(4)$

In Equations 3, 4, б_h and б_H are the minimum and maximum horizontal principal stresses (in MPa), respectively; v is Poisson’s ratio (dimensionless); б_v is the vertical in situ stress (in MPa); α is the effective stress coefficient (dimensionless); Pp is the formation pore pressure (in MPa); E is the static Young’s modulus (in MPa); ɛ_h and ɛ_H are the strains in the directions of the minimum and maximum horizontal principal stresses, respectively (dimensionless).

3.2 Establishing evaluation criteria for coal seams

Based on the fundamental geological parameters of the Baode block and combining the fracturing stimulation as well as production dynamic analysis, we conducted a comprehensive potential evaluation of the CBM wells. Accordingly, two evaluation criteria were established for comprehensive assessment of the coal seams, namely, reservoir classification and resource potential classification.

3.2.1 Reservoir classification criteria

The reservoir classification criteria were developed on the basis of two primary aspects, namely, reservoir quality and engineering quality. Reservoir quality was evaluated by selecting parameters like gas content, porosity, vitrinite content, and ash content as the classification criteria. Engineering quality was then evaluated by selecting parameters like horizontal stress difference and Poisson’s ratio as the classification criteria. By integrating reservoir quality and engineering quality, we classified the reservoirs into three categories, as shown in Table 4.

Table 4

Table 4. Comprehensive reservoir classification criteria for the coalbed methane wells in Baode block.

3.2.2 Resource potential classification criteria

Based on the reservoir classification evaluations and integrated logging–geological–engineering assessments, we established the resource potential classification standards for three types of old wells in the Baode block using key indicators like the logging parameters, reservoir conditions, structural conditions, engineering conditions, and estimated gas production. The Class I reservoirs are mainly distributed in the nose-shaped uplift areas of the local structural highs, while the Class III reservoirs are predominantly located in the trough areas of the structural lows, as shown in Table 5.

Table 5

Table 5. Resource potential classification criteria for the coalbed methane wells in Baode block.

4 Case study

The BD1 well is a typical low-production well in the Baode block; this well went into production in 2011 to target the 4 + 5 and 8 + 9 numbered coal seams, showing an average daily gas production of 460 cubic meters and a cumulative gas production of 2.45 million cubic meters prior to the intervention. Through detailed fundamental geological research, it was determined that the BD1 well was located in a local structural high within the microstructural belt of the Baode block. Comprehensive geological and engineering surveys along with production analysis indicated that there was limited remaining development potential in the original layers and no wellbore operational issues.

We conducted a comprehensive logging interpretation and evaluation in this region and found that the No. 3 coal seam in the Shanxi Formation of this well had not been effectively utilized. The proposed logging evaluation approach was applied to reinterpret the No. 3 coal seam, which revealed that the logging and engineering interpretation parameters both met Class I standards (the roof and floor of the No. 3 coal seam exhibit good sealing properties) while the reservoir parameters were primarily at Class II levels (Figure 7). Based on comprehensive analysis, the No. 3 coal seam was classified as a Class I potential layer with priority for implementation. The interpretation results and parameters for the No. 3 coal seam are presented in Table 6.

Figure 7

Figure 7. Logging interpretation results for the No. 3 coal seam in the BD1 well of Baode block.

Table 6

Table 6. Interpretation results for the reservoir, logging, and engineering parameters of the No. 3 coal seam in the BD1 well of Baode block.

In June 2023, a perforation and fracturing treatment was performed on the third coal seam of this well (perforation interval: 991–995 m), with a total fracturing fluid volume of 1,500 m³ and sand volume of 58 m³ (a larger scale than conventional fracturing). After 4 months of production drainage, the gas production of the well increased from 460 m³/d before treatment to 2,200 m³/d after treatment (Figure 8). The daily gas production levels have maintained a stable growth trend since then. As of July 2024, the cumulative incremental gas production from the treatment had reached 440,000 m³, demonstrating a significant effect.

Figure 8

Figure 8. Production performance curve of the BD1 well of Baode block.

5 Conclusion

1. The factors causing low production in the CBM wells of the Baode block include geological microstructures, reservoir fracturing scale, and wellbore integrity, among others. A comprehensive analysis was conducted using the logging, mud logging, fracturing, gas testing, production testing, and production dynamic data to identify the causes of low production in the old wells and evaluate the remaining resource potential.

2. Through integrated logging–geological–engineering research, we established key logging interpretation models and reservoir evaluation methods for the CBM wells. In this work, we developed a comprehensive evaluation method to assess the resource potentials of mature CBM wells with the aim of providing practical guidance for similar blocks as well as effective technical support for well stimulation.

3. Through a case study, we applied the proposed methods and demonstrated that the remediation measures for low-production wells in the Baode block achieved significant production enhancement. These research findings offer valuable insights and are expected to be applicable for broader implementation.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author contributions

JZ: Conceptualization, Data curation, Funding acquisition, Project administration, Writing – original draft. ZL: Methodology, Validation, Writing – review and editing. YL: Project administration, Supervision, Validation, Writing – review and editing. HG: Visualization, Writing – original draft, Writing – review and editing. RH: Data curation, Methodology, Writing – review and editing. YP: Formal Analysis, Writing – review and editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by Project 4 under Project 8 of the Ten Major Science and Technology Projects of China National Logging Corporation (“Research on Comprehensive Logging Evaluation Technology for Potential Tapping and Stable Production in Mature Oilfields”; CNLC2022-08B04). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

Conflict of interest

Authors JZ, ZL, YL, HG, RH, and YP were employed by China National Logging Corporation.

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The author(s) declared that generative AI was not used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feart.2025.1706302/full#supplementary-material

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